diff --git a/docs/api.rst b/docs/api.rst
index c527918cc..9e6f08fdd 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -336,6 +336,20 @@ For more information about fetching data from the internet, see :ref:`fetching t
    workflows.macm_workflow
    workflows.cbma_workflow
 
+:mod:`nimare.reports`: NiMARE report
+--------------------------------------------------
+
+.. automodule:: nimare.reports
+   :no-members:
+   :no-inherited-members:
+
+.. currentmodule:: nimare
+
+.. autosummary::
+   :toctree: generated/
+   :template: function.rst
+
+   reports.run_reports
 
 .. _api_base_ref:
 
diff --git a/docs/outputs.rst b/docs/outputs.rst
index 60d6ec4d1..ab25b7f62 100644
--- a/docs/outputs.rst
+++ b/docs/outputs.rst
@@ -11,11 +11,13 @@ File names
 
 NiMARE-generated files, especially ones made by meta-analyses, follow a naming convention somewhat based on BIDS.
 
-Here is the basic naming convention for statistical maps:
+Here is the basic naming convention for statistical maps and tables:
 
 .. code-block:: Text
 
-   <value>[_desc-<label>][_level-<cluster|voxel>][_corr-<FWE|FDR>][_method-<label>][_diag-<Jackknife|FocusCounter>].nii.gz
+   <value>[_desc-<label>][_level-<cluster|voxel>][_corr-<FWE|FDR>][_method-<label>][_diag-<Jackknife|FocusCounter>][_tail-<positive|negative>].nii.gz
+
+   <value>[_desc-<label>][_level-<cluster|voxel>][_corr-<FWE|FDR>][_method-<label>]_tab-<clust|counts>.tsv
 
 
 First, the ``value`` represents type of data in the map (e.g., z-statistic, t-statistic).
diff --git a/examples/02_meta-analyses/10_plot_cbma_workflow.py b/examples/02_meta-analyses/10_plot_cbma_workflow.py
index ecc56bf00..4b2cfe8ba 100644
--- a/examples/02_meta-analyses/10_plot_cbma_workflow.py
+++ b/examples/02_meta-analyses/10_plot_cbma_workflow.py
@@ -12,12 +12,13 @@
 the fundamental steps of a CBMA meta-analysis.
 """
 import os
-from pprint import pprint
+from pathlib import Path
 
 import matplotlib.pyplot as plt
 from nilearn.plotting import plot_stat_map
 
 from nimare.dataset import Dataset
+from nimare.reports.base import run_reports
 from nimare.utils import get_resource_path
 from nimare.workflows import cbma_workflow
 
@@ -75,15 +76,19 @@
 result.tables["z_corr-FDR_method-indep_diag-Jackknife_tab-counts"]
 
 ###############################################################################
-# Methods
+# Report
 # -----------------------------------------------------------------------------
-# The MetaResult object also provides boilerplate text automatically generated by NiMARE,
-# which is released under the `CC0 <https://creativecommons.org/publicdomain/zero/1.0/>`_ license.
-print("Description:")
-pprint(result.description_)
+# Finally, a NiMARE report is generated from the MetaResult.
+root_dir = Path(os.getcwd()).parents[1]
+# Use the following path to run the documentation locally:
+# html_dir = root_dir / "docs" / "_build" / "html" / "auto_examples" / "02_meta-analyses"
+html_dir = root_dir / "_readthedocs" / "html" / "auto_examples" / "02_meta-analyses"
+html_dir.mkdir(parents=True, exist_ok=True)
 
-###############################################################################
-# References
-# ``````````````````````````````````````````````````````````````````````````````
-print("References:")
-pprint(result.bibtex_)
+run_reports(result, html_dir)
+
+####################################
+# .. raw:: html
+#
+#     <iframe src="./report.html" style="border:none;" seamless="seamless" width="100%"\
+#        height="1000px"></iframe>
diff --git a/nimare/__init__.py b/nimare/__init__.py
index dd66257fd..cf9172712 100755
--- a/nimare/__init__.py
+++ b/nimare/__init__.py
@@ -16,6 +16,7 @@
         decode,
         io,
         meta,
+        reports,
         resources,
         stats,
         utils,
@@ -35,6 +36,7 @@
         "io",
         "stats",
         "utils",
+        "reports",
         "workflows",
         "__version__",
     ]
diff --git a/nimare/diagnostics.py b/nimare/diagnostics.py
index eebb97fe1..a5ed3b19e 100644
--- a/nimare/diagnostics.py
+++ b/nimare/diagnostics.py
@@ -75,30 +75,39 @@ def transform(self, result):
 
         Returns
         -------
-        contribution_table : :obj:`pandas.DataFrame` or None
-            A DataFrame with information about relative contributions of each experiment to each
-            cluster in the thresholded map.
-            There is one row for each experiment.
-            There is one column for each cluster, with column names being
-            ``PostiveTail``/``NegativeTail`` indicating the sign (+/-) of the cluster's
-            statistical values, plus an integer indicating the cluster's associated value
-            in the ``label_maps[0]``/``label_maps[1]`` output.
-            If no clusters are found or a pairwise Estimator was used, ``None`` is returned.
-        clusters_table : :obj:`pandas.DataFrame`
-            A DataFrame with information about each cluster.
-            There is one row for each cluster.
-            The columns in this table include: ``Cluster ID`` (the cluster id, plus a letter
-            for subpeaks only), ``X``/``Y``/``Z`` (coordinate for the center of mass),
-            ``Max Stat`` (statistical value of the peak), and ``Cluster Size (mm3)``
-            (the size of the cluster, in cubic millimeters).
-            If no clusters are found, this table will be empty.
-        label_maps : :obj:`list`
-            List of :obj:`nibabel.nifti1.Nifti1Image` objects of cluster label maps.
-            Each cluster in the map has a single value, which corresponds to the cluster number
-            of the column name in ``contribution_table``.
-            If target_image has negative values after thresholding, first and second maps
-            correspond to positive and negative tails.
-            If no clusters are found, this list will be empty.
+        :obj:`~nimare.results.MetaResult`
+            Results of Diagnostics fitting.
+
+        Notes
+        -----
+        This method adds two new keys to ``maps`` and ``tables`` attributes of the
+        MetaResult object.
+
+            -   ``<target_image>_diag-<Jackknife|FocusCounter>_tab-counts`` :
+                :obj:`pandas.DataFrame` or None.
+                A DataFrame with information about relative contributions of each experiment
+                to each cluster in the thresholded map.
+                There is one row for each experiment.
+                There is one column for each cluster, with column names being
+                ``PostiveTail``/``NegativeTail`` indicating the sign (+/-) of the cluster's
+                statistical values, plus an integer indicating the cluster's associated value
+                in the ``label_maps[0]``/``label_maps[1]`` output.
+                If no clusters are found or a pairwise Estimator was used, ``None`` is returned.
+            -   ``<target_image>_tab-clust`` : :obj:`pandas.DataFrame`
+                A DataFrame with information about each cluster.
+                There is one row for each cluster.
+                The columns in this table include: ``Cluster ID`` (the cluster id, plus a letter
+                for subpeaks only), ``X``/``Y``/``Z`` (coordinate for the center of mass),
+                ``Max Stat`` (statistical value of the peak), and ``Cluster Size (mm3)``
+                (the size of the cluster, in cubic millimeters).
+                If no clusters are found, this table will be empty.
+            -   ``label_<target_image>_tail-<positive|negative>`` : :obj:`numpy.ndarray`
+                Label maps.
+                Each cluster in the map has a single value, which corresponds to the cluster number
+                of the column name in ``contribution_table``.
+                If target_image has negative values after thresholding, first and second maps
+                correspond to positive and negative tails.
+                If no clusters are found, this list will be empty.
         """
         masker = result.estimator.masker
         diag_name = self.__class__.__name__
diff --git a/nimare/reports/__init__.py b/nimare/reports/__init__.py
new file mode 100644
index 000000000..fdc3f0292
--- /dev/null
+++ b/nimare/reports/__init__.py
@@ -0,0 +1,24 @@
+"""Reports module."""
+
+from .base import Report, run_reports
+from .figures import (
+    gen_table,
+    plot_clusters,
+    plot_coordinates,
+    plot_heatmap,
+    plot_interactive_brain,
+    plot_mask,
+    plot_static_brain,
+)
+
+__all__ = [
+    "Report",
+    "run_reports",
+    "gen_table",
+    "plot_clusters",
+    "plot_coordinates",
+    "plot_heatmap",
+    "plot_interactive_brain",
+    "plot_mask",
+    "plot_static_brain",
+]
diff --git a/nimare/reports/base.py b/nimare/reports/base.py
new file mode 100644
index 000000000..d577245d6
--- /dev/null
+++ b/nimare/reports/base.py
@@ -0,0 +1,479 @@
+# STATEMENT OF CHANGES: This file is derived from sources licensed under the Apache-2.0 terms,
+# and this file has been changed.
+# The original file this work derives from is found at:
+# https://github.com/nipreps/niworkflows/blob/9905f90110879ed4123ea291f512b0a60d7ba207/niworkflows/reports/core.py
+#
+# [May 2023] CHANGES:
+#    * Replace BIDSlayout with code that uses the nimare Dataset and MetaResult class.
+#
+# ORIGINAL WORK'S ATTRIBUTION NOTICE:
+#
+#     Copyright 2021 The NiPreps Developers <nipreps@gmail.com>
+#
+#     Licensed under the Apache License, Version 2.0 (the "License");
+#     you may not use this file except in compliance with the License.
+#     You may obtain a copy of the License at
+#
+#         http://www.apache.org/licenses/LICENSE-2.0
+#
+#     Unless required by applicable law or agreed to in writing, software
+#     distributed under the License is distributed on an "AS IS" BASIS,
+#     WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#     See the License for the specific language governing permissions and
+#     limitations under the License.
+"""Reports builder for NiMARE's MetaResult object."""
+import textwrap
+from glob import glob
+from pathlib import Path
+
+import jinja2
+from pkg_resources import resource_filename as pkgrf
+
+from nimare.meta.cbma.base import CBMAEstimator
+from nimare.reports.figures import (
+    gen_table,
+    plot_clusters,
+    plot_coordinates,
+    plot_heatmap,
+    plot_interactive_brain,
+    plot_mask,
+    plot_static_brain,
+)
+
+SVG_SNIPPET = [
+    """\
+    <object class="svg-reportlet" type="image/svg+xml" data="./{0}">
+    Problem loading figure {0}. If the link below works, please try \
+    reloading the report in your browser.</object>
+    </div>
+    <div class="elem-filename">
+        Get figure file: <a href="./{0}" target="_blank">{0}</a>
+    </div>
+    """,
+    """\
+    <img class="svg-reportlet" src="./{0}" style="width: 100%" />
+    </div>
+    <div class="elem-filename">
+        Get figure file: <a href="./{0}" target="_blank">{0}</a>
+    </div>
+    """,
+]
+
+IFRAME_SNIPPET = """\
+<iframe id="igraph" scrolling="no" style="border:none;" seamless="seamless" \
+src="./{0}" height="800" width="100%"></iframe>
+"""
+
+PARAMETERS_DICT = {
+    "kernel_transformer__fwhm": "FWHM",
+    "kernel_transformer__sample_size": "Sample size",
+    "kernel_transformer__r": "Sphere radius (mm)",
+    "kernel_transformer__value": "Value for sphere",
+    "null_method": "Null method",
+    "n_iters": "Number of iterations",
+    "n_cores": "Number of cores",
+    "fwe": "Family-wise error rate (FWE) correction",
+    "fdr": "False discovery rate (FDR) correction",
+    "method": "Method",
+    "alpha": "Alpha",
+}
+
+SUMMARY_TEMPLATE = """\
+<ul class="elem-desc">
+<li>Number of studies: {n_exps:d}</li>
+<li>Number of studies included: {n_exps_sel:d}</li>
+<li>Number of foci: {n_foci:d} </li>
+<li>Number of foci outside the mask: {n_foci_nonbrain:d} </li>
+</ul>
+<details>
+<summary>Studies excluded</summary><br />
+<p>{exc_ids}</p>
+</details>
+"""
+
+ESTIMATOR_TEMPLATE = """\
+<ul class="elem-desc">
+<li>Kernel Transformer: {kernel_transformer}{ker_params_text}</li>
+{est_params_text}
+</ul>
+"""
+
+CORRECTOR_TEMPLATE = """\
+<ul class="elem-desc">
+<li> Correction Method: {correction_method}</li>
+{cor_params_text}
+<li>Parameters: {ext_params_text}</li>
+</ul>
+"""
+
+DIAGNOSTIC_TEMPLATE = """\
+<h2 class="sub-report-group">Target image: {target_image}</h2>
+<ul class="elem-desc">
+<li>Voxel-level threshold: {voxel_thresh}</li>
+<li>Cluster size threshold: {cluster_threshold}</li>
+<li>Number of cores: {n_cores}</li>
+</ul>
+"""
+
+
+def _gen_est_summary(obj, out_filename):
+    """Generate html with parameter use in obj (e.g., estimator)."""
+    params_dict = obj.get_params()
+    est_params = {k: v for k, v in params_dict.items() if not k.startswith("kernel_transformer")}
+    ker_params = {k: v for k, v in params_dict.items() if k.startswith("kernel_transformer__")}
+
+    ker_params_text = ["<ul>"]
+    for k, v in ker_params.items():
+        ker_params_text.append(f"<li>{PARAMETERS_DICT[k]}: {v}</li>")
+    ker_params_text.append("</ul>")
+    ker_params_text = "".join(ker_params_text)
+
+    est_params_text = []
+    for k, v in est_params.items():
+        est_params_text.append(f"<li>{PARAMETERS_DICT[k]}: {v}</li>")
+    est_params_text = "".join(est_params_text)
+
+    summary_text = ESTIMATOR_TEMPLATE.format(
+        kernel_transformer=str(params_dict["kernel_transformer"]),
+        ker_params_text=ker_params_text,
+        est_params_text=est_params_text,
+    )
+    (out_filename).write_text(summary_text, encoding="UTF-8")
+
+
+def _gen_cor_summary(obj, out_filename):
+    """Generate html with parameter use in obj (e.g., corrector)."""
+    params_dict = obj.get_params()
+
+    cor_params_text = []
+    for k, v in params_dict.items():
+        cor_params_text.append(f"<li>{PARAMETERS_DICT[k]}: {v}</li>")
+    cor_params_text = "".join(cor_params_text)
+
+    ext_params_text = ["<ul>"]
+    for k, v in obj.parameters.items():
+        ext_params_text.append(f"<li>{PARAMETERS_DICT[k]}: {v}</li>")
+    ext_params_text.append("</ul>")
+    ext_params_text = "".join(ext_params_text)
+
+    summary_text = CORRECTOR_TEMPLATE.format(
+        correction_method=PARAMETERS_DICT[obj._correction_method],
+        cor_params_text=cor_params_text,
+        ext_params_text=ext_params_text,
+    )
+    (out_filename).write_text(summary_text, encoding="UTF-8")
+
+
+def _gen_diag_summary(obj, out_filename):
+    """Generate html with parameter use in obj (e.g., diagnostics)."""
+    diag_dict = obj.get_params()
+
+    summary_text = DIAGNOSTIC_TEMPLATE.format(**diag_dict)
+    (out_filename).write_text(summary_text, encoding="UTF-8")
+
+
+def _no_clusts_found(out_filename):
+    """Generate html with single text."""
+    null_text = '<h4 style="color:#A30000">No significant clusters found</h4>'
+    (out_filename).write_text(null_text, encoding="UTF-8")
+
+
+def _no_maps_found(out_filename):
+    """Generate html with single text."""
+    null_text = """\
+    <h4 style="color:#A30000">No significant voxels were found above the threshold</h4>
+    """
+    (out_filename).write_text(null_text, encoding="UTF-8")
+
+
+def _gen_fig_summary(img_key, threshold, out_filename):
+    summary_text = f"""\
+    <h2 class="sub-report-group">Corrected meta-analytic map: {img_key}</h2>
+    <ul class="elem-desc">
+    <li>Voxel-level threshold: {threshold}</li>
+    </ul>
+    """
+    (out_filename).write_text(summary_text, encoding="UTF-8")
+
+
+def _gen_summary(dset, out_filename):
+    """Generate preliminary checks from dataset for the report."""
+    mask = dset.masker.mask_img
+    sel_ids = dset.get_studies_by_mask(mask)
+    sel_dset = dset.slice(sel_ids)
+
+    n_foci = dset.coordinates.shape[0]
+    n_foci_sel = sel_dset.coordinates.shape[0]
+    n_foci_nonbrain = n_foci - n_foci_sel
+
+    n_exps = len(dset.ids)
+    n_exps_sel = len(sel_dset.ids)
+    exc_ids = list(set(dset.ids) - set(sel_dset.ids))
+    exc_ids_str = ", ".join(exc_ids)
+
+    summary_text = SUMMARY_TEMPLATE.format(
+        n_exps=n_exps,
+        n_exps_sel=n_exps_sel,
+        n_foci=n_foci,
+        n_foci_nonbrain=n_foci_nonbrain,
+        exc_ids=exc_ids_str,
+    )
+    (out_filename).write_text(summary_text, encoding="UTF-8")
+
+
+def _gen_figures(results, img_key, diag_name, threshold, fig_dir):
+    """Generate html and png objects for the report."""
+    # Plot brain images if not empty
+    if (results.maps[img_key] > threshold).any():
+        img = results.get_map(img_key)
+        plot_interactive_brain(img, fig_dir / "corrector_figure-interactive.html", threshold)
+        plot_static_brain(img, fig_dir / "corrector_figure-static.png", threshold)
+    else:
+        _no_maps_found(fig_dir / "corrector_figure-non.html")
+
+    # Plot clusters table if cluster_table is not empty
+    cluster_table = results.tables[f"{img_key}_tab-clust"]
+    if cluster_table is not None and not cluster_table.empty:
+        gen_table(cluster_table, fig_dir / "diagnostics_tab-clust_table.html")
+
+        # Get label maps
+        lbl_name = "_".join(img_key.split("_")[1:])
+        lbl_name = "_" + lbl_name if lbl_name else lbl_name
+        for tail in ["positive", "negative"]:
+            lbl_key = f"label{lbl_name}_tail-{tail}"
+            if lbl_key in results.maps:
+                label_map = results.get_map(lbl_key)
+                plot_clusters(label_map, fig_dir / f"diagnostics_tail-{tail}_figure.png")
+
+    else:
+        _no_clusts_found(fig_dir / "diagnostics_tab-clust_table.html")
+
+    # Plot heatmap if contribution_table is not empty
+    if f"{img_key}_diag-{diag_name}_tab-counts" in results.tables:
+        contribution_table = results.tables[f"{img_key}_diag-{diag_name}_tab-counts"]
+        if contribution_table is not None and not contribution_table.empty:
+            contribution_table = contribution_table.set_index("id")
+            plot_heatmap(
+                contribution_table,
+                fig_dir / f"diagnostics_diag-{diag_name}_tab-counts_figure.html",
+            )
+
+
+class Element(object):
+    """Just a basic component of a report."""
+
+    def __init__(self, name, title=None):
+        self.name = name
+        self.title = title
+
+
+class Reportlet(Element):
+    """Reportlet holds the content of a SubReports.
+
+    A reportlet has title, description and a list of components with either an
+    HTML fragment or a path to an SVG file, and possibly a caption. This is a
+    factory class to generate Reportlets reusing the config object from a ``Report``
+    object.
+    """
+
+    def __init__(self, out_dir, config=None):
+        if not config:
+            raise RuntimeError("Reportlet must have a config object")
+
+        bids_dict = config["bids"]
+
+        # value and suffix are don't need the key, so removing from the bids conform name
+        keys_to_skip = ["value", "suffix"]
+        bids_name = "_".join("%s-%s" % i for i in bids_dict.items() if i[0] not in keys_to_skip)
+        bids_name = f"_{bids_name}" if bids_name else bids_name
+        bids_name = f"{bids_dict['value']}{bids_name}_{bids_dict['suffix']}"
+
+        self.name = config.get("name", bids_name)
+        self.title = config.get("title")
+        self.subtitle = config.get("subtitle")
+        self.description = config.get("description")
+
+        files = glob(str(out_dir / "figures" / f"{self.name}.*"))
+
+        self.components = []
+        for file in files:
+            src = Path(file)
+            ext = "".join(src.suffixes)
+            desc_text = config.get("caption")
+            iframe = config.get("iframe", False)
+
+            contents = None
+            html_anchor = src.relative_to(out_dir)
+            if ext == ".html":
+                contents = IFRAME_SNIPPET.format(html_anchor) if iframe else src.read_text()
+            elif ext == ".png":
+                contents = SVG_SNIPPET[config.get("static", True)].format(html_anchor)
+
+            if contents:
+                self.components.append((contents, desc_text))
+
+    def is_empty(self):
+        """Check if the reportlet has no components."""
+        return len(self.components) == 0
+
+
+class SubReport(Element):
+    """SubReports are sections within a Report."""
+
+    def __init__(self, name, isnested=False, reportlets=None, title=""):
+        self.name = name
+        self.title = title
+        self.reportlets = reportlets or []
+        self.isnested = isnested
+
+
+class Report:
+    """The full report object.
+
+    .. versionadded:: 0.1.0
+
+    Parameters
+    ----------
+    result : :obj:`~nimare.results.MetaResult`
+        A MetaResult produced by a coordinate- or image-based meta-analysis.
+    out_dir : :obj:`str`
+        Output directory in which to save the report.
+    out_filename : :obj:`str`, optional
+        The name of an html file to export the report to.
+        Default is 'report.html'.
+    """
+
+    def __init__(
+        self,
+        results,
+        out_dir,
+        out_filename="report.html",
+    ):
+        self.results = results
+
+        # Initialize structuring elements
+        self.sections = []
+        self.out_dir = Path(out_dir)
+        self.out_filename = out_filename
+
+        self.fig_dir = self.out_dir / "figures"
+        self.fig_dir.mkdir(parents=True, exist_ok=True)
+
+        # Generate summary text
+        _gen_summary(self.results.estimator.dataset, self.fig_dir / "preliminary_summary.html")
+
+        # Plot mask
+        plot_mask(
+            self.results.estimator.dataset.masker.mask_img,
+            self.fig_dir / "preliminary_figure-mask.png",
+        )
+
+        if issubclass(type(self.results.estimator), CBMAEstimator):
+            # Plot coordinates for CBMA estimators
+            plot_coordinates(
+                self.results.estimator.dataset.coordinates,
+                self.fig_dir / "preliminary_figure-static.png",
+                self.fig_dir / "preliminary_figure-interactive.html",
+                self.fig_dir / "preliminary_figure-legend.png",
+            )
+
+        _gen_est_summary(self.results.estimator, self.fig_dir / "estimator_summary.html")
+        _gen_cor_summary(self.results.corrector, self.fig_dir / "corrector_summary.html")
+        for diagnostic in self.results.diagnostics:
+            img_key = diagnostic.target_image
+            diag_name = diagnostic.__class__.__name__
+            threshold = diagnostic.voxel_thresh
+
+            _gen_fig_summary(img_key, threshold, self.fig_dir / "corrector_fig-summary.html")
+            _gen_diag_summary(
+                diagnostic, self.fig_dir / f"diagnostics_diag-{diag_name}_summary.html"
+            )
+            _gen_figures(self.results, img_key, diag_name, threshold, self.fig_dir)
+
+        # Default template from nimare
+        self.template_path = Path(pkgrf("nimare", "reports/report.tpl"))
+        self._load_config(Path(pkgrf("nimare", "reports/default.yml")))
+        assert self.template_path.exists()
+
+    def _load_config(self, config):
+        from yaml import safe_load as load
+
+        settings = load(config.read_text())
+        self.packagename = settings.get("package", None)
+
+        self.index(settings["sections"])
+
+    def index(self, config):
+        """Traverse the reports config definition and instantiate reportlets.
+
+        This method also places figures in their final location.
+        """
+        for subrep_cfg in config:
+            reportlets = [Reportlet(self.out_dir, config=cfg) for cfg in subrep_cfg["reportlets"]]
+
+            # Filter out empty reportlets
+            reportlets = [r for r in reportlets if not r.is_empty()]
+            if reportlets:
+                sub_report = SubReport(
+                    subrep_cfg["name"],
+                    isnested=False,
+                    reportlets=reportlets,
+                    title=subrep_cfg.get("title"),
+                )
+                self.sections.append(sub_report)
+
+    def generate_report(self):
+        """Once the Report has been indexed, the final HTML can be generated."""
+        boilerplate = []
+        boiler_idx = 0
+
+        if hasattr(self.results, "description_"):
+            text = self.results.description_
+            references = self.results.bibtex_
+            text = textwrap.fill(text, 99)
+
+            boilerplate.append(
+                (
+                    boiler_idx,
+                    "LaTeX",
+                    f"""<pre>{text}</pre>
+                        <h3>Bibliography</h3>
+                        <pre>{references}</pre>
+                    """,
+                )
+            )
+            boiler_idx += 1
+
+        env = jinja2.Environment(
+            loader=jinja2.FileSystemLoader(searchpath=str(self.template_path.parent)),
+            trim_blocks=True,
+            lstrip_blocks=True,
+            autoescape=False,
+        )
+        report_tpl = env.get_template(self.template_path.name)
+        report_render = report_tpl.render(sections=self.sections, boilerplate=boilerplate)
+
+        # Write out report
+        self.out_dir.mkdir(parents=True, exist_ok=True)
+        (self.out_dir / self.out_filename).write_text(report_render, encoding="UTF-8")
+
+
+def run_reports(
+    results,
+    out_dir,
+):
+    """Run the reports.
+
+    .. versionadded:: 0.1.0
+
+    Parameters
+    ----------
+    result : :obj:`~nimare.results.MetaResult`
+        A MetaResult produced by a coordinate- or image-based meta-analysis.
+    out_dir : :obj:`str`
+        Output directory in which to save the report.
+    """
+    return Report(
+        results,
+        out_dir,
+    ).generate_report()
diff --git a/nimare/reports/default.yml b/nimare/reports/default.yml
new file mode 100644
index 000000000..b9a039d1c
--- /dev/null
+++ b/nimare/reports/default.yml
@@ -0,0 +1,85 @@
+# STATEMENT OF CHANGES: This file is derived from sources licensed under the Apache-2.0 terms,
+# and this file has been changed.
+# The original file this work derives from is found at:
+# https://github.com/nipreps/niworkflows/blob/9905f90110879ed4123ea291f512b0a60d7ba207/niworkflows/reports/default.yml
+#
+# [May 2023] CHANGES:
+#    * Replace BIDSlayout with code that uses the nimare Dataset and MetaResult class.
+#
+# ORIGINAL WORK'S ATTRIBUTION NOTICE:
+#
+#     Copyright 2021 The NiPreps Developers <nipreps@gmail.com>
+#
+#     Licensed under the Apache License, Version 2.0 (the "License");
+#     you may not use this file except in compliance with the License.
+#     You may obtain a copy of the License at
+#
+#         http://www.apache.org/licenses/LICENSE-2.0
+#
+#     Unless required by applicable law or agreed to in writing, software
+#     distributed under the License is distributed on an "AS IS" BASIS,
+#     WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#     See the License for the specific language governing permissions and
+#     limitations under the License.
+define: &heatmap_text "The heatmap presents the relative contributions of each experiment to 
+      each cluster in the thresholded map. There is one row for each experiment, and 
+      one column for each cluster, with column names being 
+      <em>PostiveTail</em>/<em>NegativeTail</em> indicating the sign (+/-) of the cluster's
+      statistical values. The rows and columns were re-ordered to form clusters in the heatmap."
+define: &focuscounter_text "The FocusCounter analysis characterizes the relative contribution 
+      of each experiment in a meta-analysis to the resulting clusters by counting the number 
+      of peaks from each experiment that fall within each significant cluster."
+define: &jackknife_text "The Jackknife analysis characterizes the relative contribution of each 
+      experiment in a meta-analysis to the resulting clusters by looping through 
+      experiments, calculating the Estimator's summary statistic for all experiments 
+      <b>except</b> the target experiment, dividing the resulting test summary statistics 
+      by the summary statistics from the original meta-analysis, and finally averaging 
+      the resulting proportion values across all voxels in each cluster."
+define: &explorer_text "The following figure provides an interactive window to explore 
+      the meta-analytic map in detail."
+package: nimare
+sections:
+- name: Summary
+  reportlets:
+  - bids: {value: preliminary, suffix: summary}
+  - bids: {value: preliminary, suffix: figure-mask}
+    title: Mask
+  - bids: {value: preliminary, suffix: figure-static}
+    title: Peak coordinates
+  - bids: {value: preliminary, suffix: figure-legend}
+  - bids: {value: preliminary, suffix: figure-interactive}
+    title: Explorer
+- name: Meta-Analysis
+  reportlets:
+  - bids: {value: estimator, suffix: summary}
+    title: Estimator
+    description: Parameters use to fit the meta-analytic estimator.
+  - bids: {value: corrector, suffix: summary}
+    title: Corrector
+    description: Parameters use to fit the corrector.
+  - bids: {value: corrector, suffix: fig-summary}
+  - bids: {value: corrector, suffix: figure-non}
+  - bids: {value: corrector, suffix: figure-interactive}
+    subtitle: Explorer
+    description: *explorer_text
+  - bids: {value: corrector, suffix: figure-static}
+    description: This panel shows the the corrrected meta-analytic map.
+- name: Diagnostics
+  reportlets:
+  - bids: {value: diagnostics, suffix: diag-summary}
+  - bids: {value: diagnostics, tab: clust, suffix: table}
+    subtitle: Significant clusters
+  - bids: {value: diagnostics, tail: positive, suffix: figure}
+    subtitle: "Label map: positive tail"
+  - bids: {value: diagnostics, tail: negative, suffix: figure}
+    subtitle: "Label map: negative tail"
+  - bids: {value: diagnostics, diag: FocusCounter, tab: counts, suffix: figure}
+    subtitle: FocusCounter
+    caption: *heatmap_text
+    description: *focuscounter_text
+    iframe: True
+  - bids: {value: diagnostics, diag: Jackknife, tab: counts, suffix: figure}
+    subtitle: Jackknife
+    caption: *heatmap_text
+    description: *jackknife_text
+    iframe: True
\ No newline at end of file
diff --git a/nimare/reports/figures.py b/nimare/reports/figures.py
new file mode 100644
index 000000000..ff4e13d9e
--- /dev/null
+++ b/nimare/reports/figures.py
@@ -0,0 +1,354 @@
+"""Plot figures for report."""
+import matplotlib.colors as mcolors
+import matplotlib.patches as mpatches
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+import plotly.express as px
+from nilearn import datasets
+from nilearn.plotting import (
+    plot_connectome,
+    plot_roi,
+    plot_stat_map,
+    view_connectome,
+    view_img,
+)
+from scipy.cluster.hierarchy import leaves_list, linkage, optimal_leaf_ordering
+
+TABLE_STYLE = [
+    dict(
+        selector="th, td",
+        props=[
+            ("text-align", "center"),
+            ("font-family", "monospace"),
+            ("font-size", "15px"),
+            ("padding", "5px 3px"),
+            ("margin", "0px 3px"),
+            ("border", "1px solid #ddd"),
+        ],
+    ),
+]
+
+
+def _check_extention(filename, exts):
+    if filename.suffix not in exts:
+        raise ValueError(
+            f'The "out_filename" provided has extension {filename.suffix}. '
+            f'Valid extensions are {", ".join(exts)}.'
+        )
+
+
+def _reorder_matrix(mat, row_labels, col_labels, reorder):
+    """Reorder a matrix.
+
+    This function reorders the provided matrix. It was adaptes from
+    nilearn.plotting.plot_matrix._reorder_matrix to reorder non-square matrices.
+
+        License
+    -------
+    New BSD License
+    Copyright (c) 2007 - 2023 The nilearn developers.
+    Redistribution and use in source and binary forms, with or without
+    modification, are permitted provided that the following conditions are met:
+    a. Redistributions of source code must retain the above copyright notice,
+        this list of conditions and the following disclaimer.
+    b. Redistributions in binary form must reproduce the above copyright
+        notice, this list of conditions and the following disclaimer in the
+        documentation and/or other materials provided with the distribution.
+    c. Neither the name of the nilearn developers nor the names of
+        its contributors may be used to endorse or promote products
+        derived from this software without specific prior written
+        permission.
+    THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+    AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+    IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+    ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR
+    ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+    DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+    SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+    CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+    LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
+    OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH
+    DAMAGE.
+    """
+    if not row_labels or not col_labels:
+        raise ValueError("Labels are needed to show the reordering.")
+
+    # Order rows
+    row_linkage_matrix = linkage(mat, method=reorder)
+    row_ordered_linkage = optimal_leaf_ordering(row_linkage_matrix, mat)
+    row_index = leaves_list(row_ordered_linkage)
+
+    # Order columns
+    col_linkage_matrix = linkage(mat.T, method=reorder)
+    col_ordered_linkage = optimal_leaf_ordering(col_linkage_matrix, mat)
+    col_index = leaves_list(col_ordered_linkage)
+
+    # Make sure labels is an ndarray and copy it
+    row_labels = np.array(row_labels).copy()
+    col_labels = np.array(col_labels).copy()
+    mat = mat.copy()
+
+    # and reorder labels and matrix
+    row_labels = row_labels[row_index].tolist()
+    col_labels = col_labels[col_index].tolist()
+    mat = mat[row_index, :][:, col_index]
+
+    return mat, row_labels, col_labels
+
+
+def plot_static_brain(img, out_filename, threshold=1e-06):
+    """Plot static brain image.
+
+    .. versionadded:: 0.1.0
+
+    Parameters
+    ----------
+    img : :obj:`~nibabel.nifti1.Nifti1Image`
+        Stat image to plot.
+    out_filename : :obj:`pathlib.Path`
+        The name of an image file to export the plot to.
+        Valid extensions are '.png', '.pdf', '.svg'.
+    threshold: a number, None, or 'auto', optional
+        If None is given, the image is not thresholded. If a number is given, it is
+        used to threshold the image: values below the threshold (in absolute value)
+        are plotted as transparent. If 'auto' is given, the threshold is determined
+        magically by analysis of the image. Default=1e-6.
+    """
+    _check_extention(out_filename, [".png", ".pdf", ".svg"])
+
+    template = datasets.load_mni152_template(resolution=1)
+    fig = plot_stat_map(
+        img,
+        bg_img=template,
+        black_bg=False,
+        draw_cross=False,
+        threshold=threshold,
+        vmax=4,
+        display_mode="mosaic",
+    )
+    fig.savefig(out_filename, dpi=300)
+    fig.close()
+
+
+def plot_mask(mask, out_filename):
+    """Plot mask.
+
+    .. versionadded:: 0.1.0
+
+    Parameters
+    ----------
+    img : :obj:`~nibabel.nifti1.Nifti1Image`
+        Mask image to plot.
+    out_filename : :obj:`pathlib.Path`
+        The name of an image file to export the plot to.
+        Valid extensions are '.png', '.pdf', '.svg'.
+    """
+    _check_extention(out_filename, [".png", ".pdf", ".svg"])
+
+    template = datasets.load_mni152_template(resolution=1)
+
+    fig = plot_roi(
+        mask,
+        bg_img=template,
+        black_bg=False,
+        draw_cross=False,
+        cmap="tab20",
+        alpha=0.7,
+        display_mode="mosaic",
+    )
+    fig.savefig(out_filename, dpi=300)
+    fig.close()
+
+
+def plot_coordinates(
+    coordinates_df, out_static_filename, out_interactive_filename, out_legend_filename
+):
+    """Plot static and interactive coordinates.
+
+    .. versionadded:: 0.1.0
+
+    Parameters
+    ----------
+    coordinates_df : :obj:`pandas.DataFrame`
+        A DataFrame with the coordinates in the dataset.
+    out_static_filename : :obj:`pathlib.Path`
+        The name of an image file to export the static plot to.
+        Valid extensions are '.png', '.pdf', '.svg'.
+    out_interactive_filename : :obj:`pathlib.Path`
+        The name of an image file to export the interactive plot to.
+        Valid extension is '.html'.
+    out_legend_filename : :obj:`pathlib.Path`
+        The name of an image file to export the legend plot to.
+        Valid extensions are '.png', '.pdf', '.svg'.
+    """
+    _check_extention(out_static_filename, [".png", ".pdf", ".svg"])
+    _check_extention(out_interactive_filename, [".html"])
+    _check_extention(out_legend_filename, [".png", ".pdf", ".svg"])
+
+    node_coords = coordinates_df[["x", "y", "z"]].to_numpy()
+    n_coords = len(node_coords)
+    adjacency_matrix = np.zeros((n_coords, n_coords))
+
+    # Generate dictionary and array of colors for each unique ID
+    ids = coordinates_df["id"].to_list()
+    unq_ids = np.unique(ids)
+    cmap = plt.cm.get_cmap("tab20", len(unq_ids))
+    colors_dict = {unq_id: mcolors.to_hex(cmap(i)) for i, unq_id in enumerate(unq_ids)}
+    colors = [colors_dict[id_] for id_ in ids]
+
+    fig = plot_connectome(adjacency_matrix, node_coords, node_color=colors)
+    fig.savefig(out_static_filename, dpi=300)
+    fig.close()
+
+    # Generate legend
+    patches_lst = [
+        mpatches.Patch(color=color, label=label) for label, color in colors_dict.items()
+    ]
+
+    # Plot legeng
+    ncol = 10
+    labl_fig, ax = plt.subplots(1, 1)
+    labl_fig.set_size_inches(ncol, len(patches_lst) / ncol**2)
+    labl_fig.legend(
+        handles=patches_lst,
+        ncol=ncol,
+        fontsize=10,
+        loc="center",
+    )
+    ax.axis("off")
+    labl_fig.savefig(out_legend_filename, bbox_inches="tight", dpi=300)
+    plt.close()
+
+    # Plot interactive connectome
+    html_view = view_connectome(
+        adjacency_matrix,
+        node_coords,
+        node_size=10,
+        colorbar=False,
+        node_color=colors,
+    )
+    html_view.save_as_html(out_interactive_filename)
+
+
+def plot_interactive_brain(img, out_filename, threshold=1e-06):
+    """Plot interactive brain image.
+
+    .. versionadded:: 0.1.0
+
+    Parameters
+    ----------
+    img : :obj:`~nibabel.nifti1.Nifti1Image`
+        Stat image to plot.
+    out_filename : :obj:`pathlib.Path`
+        The name of an image file to export the plot to. Valid extension is '.html'.
+    threshold: a number, None, or 'auto', optional
+        If None is given, the image is not thresholded. If a number is given, it is
+        used to threshold the image: values below the threshold (in absolute value)
+        are plotted as transparent. If 'auto' is given, the threshold is determined
+        magically by analysis of the image. Default=1e-6.
+    """
+    _check_extention(out_filename, [".html"])
+
+    template = datasets.load_mni152_template(resolution=1)
+    html_view = view_img(img, bg_img=template, black_bg=False, threshold=threshold, vmax=4)
+    html_view.save_as_html(out_filename)
+
+
+def plot_heatmap(contribution_table, out_filename):
+    """Plot heatmap.
+
+    .. versionadded:: 0.1.0
+
+    Parameters
+    ----------
+    contribution_table : :obj:`pandas.DataFrame`
+        A DataFrame with information about relative contributions of each experiment to each
+        cluster in the thresholded map.
+    out_filename : :obj:`pathlib.Path`
+        The name of an image file to export the plot to.
+        Valid extension is '.html'.
+    """
+    _check_extention(out_filename, [".html"])
+
+    mat = contribution_table.to_numpy()
+    row_labels, col_labels = (
+        contribution_table.index.to_list(),
+        contribution_table.columns.to_list(),
+    )
+
+    new_mat, new_row_labels, new_col_labels = _reorder_matrix(
+        mat,
+        row_labels,
+        col_labels,
+        "single",
+    )
+    new_df = pd.DataFrame(new_mat, columns=new_col_labels, index=new_row_labels)
+
+    fig = px.imshow(new_df, color_continuous_scale="Reds")
+    fig.update_layout(
+        autosize=False,
+        width=800,
+        height=800,
+    )
+    fig.write_html(out_filename, full_html=True, include_plotlyjs=True)
+
+
+def gen_table(clusters_table, out_filename):
+    """Generate table.
+
+    .. versionadded:: 0.1.0
+
+    Parameters
+    ----------
+    clusters_table : :obj:`pandas.DataFrame`
+        A DataFrame with information about each cluster.
+    out_filename : :obj:`pathlib.Path`
+        The name of an image file to export the plot to.
+        Valid extension is '.html'.
+    """
+    _check_extention(out_filename, [".html"])
+
+    clust_ids = clusters_table["Cluster ID"].to_list()
+    clusters_table = clusters_table.drop(columns=["Cluster ID"])
+
+    tail = [c_id.split(" ")[0].split("Tail")[0] for c_id in clust_ids]
+    ids = [c_id.split(" ")[1] for c_id in clust_ids]
+    tuples = list(zip(*[tail, ids]))
+    row = pd.MultiIndex.from_tuples(tuples)
+    clusters_table.index = row
+    clusters_table.index = clusters_table.index.rename(["Tail", "Cluster ID"])
+
+    styled_df = clusters_table.style.format(precision=2).set_table_styles(TABLE_STYLE)
+    styled_df.to_html(out_filename)
+
+
+def plot_clusters(img, out_filename):
+    """Plot clusters.
+
+    .. versionadded:: 0.1.0
+
+    Parameters
+    ----------
+    img : :obj:`~nibabel.nifti1.Nifti1Image`
+        Label image to plot.
+    out_filename : :obj:`pathlib.Path`
+        The name of an image file to export the plot to.
+        Valid extensions are '.png', '.pdf', '.svg'.
+    """
+    _check_extention(out_filename, [".png", ".pdf", ".svg"])
+
+    template = datasets.load_mni152_template(resolution=1)
+
+    fig = plot_roi(
+        img,
+        bg_img=template,
+        black_bg=False,
+        draw_cross=False,
+        cmap="tab20",
+        alpha=0.8,
+        colorbar=True,
+        display_mode="mosaic",
+    )
+    fig.savefig(out_filename, dpi=300)
+    fig.close()
diff --git a/nimare/reports/report.tpl b/nimare/reports/report.tpl
new file mode 100644
index 000000000..cbf8ca619
--- /dev/null
+++ b/nimare/reports/report.tpl
@@ -0,0 +1,140 @@
+<?xml version="1.0" encoding="utf-8" ?>
+<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
+<html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en">
+<head>
+<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
+<meta name="generator" content="Docutils 0.12: http://docutils.sourceforge.net/" />
+<title></title>
+<script src="https://code.jquery.com/jquery-3.3.1.slim.min.js" integrity="sha384-q8i/X+965DzO0rT7abK41JStQIAqVgRVzpbzo5smXKp4YfRvH+8abtTE1Pi6jizo" crossorigin="anonymous"></script>
+<script src="https://stackpath.bootstrapcdn.com/bootstrap/4.1.3/js/bootstrap.min.js" integrity="sha384-ChfqqxuZUCnJSK3+MXmPNIyE6ZbWh2IMqE241rYiqJxyMiZ6OW/JmZQ5stwEULTy" crossorigin="anonymous"></script>
+<link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.1.3/css/bootstrap.min.css" integrity="sha384-MCw98/SFnGE8fJT3GXwEOngsV7Zt27NXFoaoApmYm81iuXoPkFOJwJ8ERdknLPMO" crossorigin="anonymous">
+<style type="text/css">
+.sub-report-title {}
+.run-title {}
+
+h1 { padding-top: 35px; }
+h2 { padding-top: 20px; }
+h3 { padding-top: 15px; }
+
+.elem-desc {}
+.elem-caption {
+    margin-top: 15px
+    margin-bottom: 0;
+}
+.elem-filename {}
+
+div.elem-image {
+  width: 100%;
+  page-break-before:always;
+}
+
+.elem-image object.svg-reportlet {
+    width: 100%;
+    padding-bottom: 5px;
+}
+body {
+    padding: 65px 10px 10px;
+}
+
+.boiler-html {
+    font-family: "Bitstream Charter", "Georgia", Times;
+    margin: 20px 25px;
+    padding: 10px;
+    background-color: #F8F9FA;
+}
+
+div#boilerplate pre {
+    margin: 20px 25px;
+    padding: 10px;
+    background-color: #F8F9FA;
+}
+
+#errors div, #errors p {
+    padding-left: 1em;
+}
+</style>
+</head>
+<body>
+
+
+<nav class="navbar fixed-top navbar-expand-lg navbar-light bg-light">
+<div class="collapse navbar-collapse">
+    <ul class="navbar-nav">
+    {% for sub_report in sections %}
+        {% if sub_report.isnested %}
+        <li class="nav-item dropdown">
+            <a class="nav-link dropdown-toggle" id="navbar{{ sub_report.name }}" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false" href="#">{{ sub_report.name }}</a>
+            <div class="dropdown-menu" aria-labelledby="navbar{{ sub_report.name }}">
+                {% for run_report in sub_report.reportlets %}
+                    {% if run_report.title %}
+                    <a class="dropdown-item" href="#{{run_report.name}}">{{run_report.title}}</a>
+                    {% endif %}
+                {% endfor %}
+            </div>
+        </li>
+        {% else %}
+        <li class="nav-item"><a class="nav-link" href="#{{sub_report.name}}">{{sub_report.name}}</a></li>
+        {% endif %}
+    {% endfor %}
+        <li class="nav-item"><a class="nav-link" href="#boilerplate">Methods</a></li>
+    </ul>
+</div>
+</nav>
+<noscript>
+    <h1 class="text-danger"> The navigation menu uses Javascript. Without it this report might not work as expected </h1>
+</noscript>
+
+{% for sub_report in sections %}
+    {% if sub_report.reportlets %}
+    <div id="{{ sub_report.name }}">
+    <h1 class="sub-report-title">{{ sub_report.name }}</h1>
+    {% for run_report in sub_report.reportlets %}
+        <div id="{{run_report.name}}">
+            {% if run_report.title %}<h2 class="sub-report-group">{{ run_report.title }}</h2>{% endif %}
+            {% if run_report.subtitle %}<h3 class="run-title">{{ run_report.subtitle }}</h3>{% endif %}
+            {% if run_report.description %}<p class="elem-desc">{{ run_report.description }}</p>{% endif %}
+            {% for elem in run_report.components %}
+                {% if elem[0] %}
+                    {% if elem[1] %}<p class="elem-caption">{{ elem[1] }}</p>{% endif %}
+                    {{ elem[0] }}
+                {% endif %}
+            {% endfor %}
+        </div>
+    {% endfor %}
+    </div>
+    {% endif %}
+{% endfor %}
+
+<div id="boilerplate">
+    <h1 class="sub-report-title">Methods</h1>
+    {% if boilerplate %}
+    <p>We kindly ask to report results preprocessed with this tool using the following
+       boilerplate.</p>
+    <ul class="nav nav-tabs" id="myTab" role="tablist">
+        {% for b in boilerplate %}
+        <li class="nav-item">
+            <a class="nav-link {% if b[0] == 0 %}active{% endif %}" id="{{ b[1] }}-tab" data-toggle="tab" href="#{{ b[1] }}" role="tab" aria-controls="{{ b[1] }}" aria-selected="{% if b[0] == 0 %}true{%else%}false{% endif %}">{{ b[1] }}</a>
+        </li>
+        {% endfor %}
+    </ul>
+    <div class="tab-content" id="myTabContent">
+      {% for b in boilerplate %}
+      <div class="tab-pane fade {% if b[0] == 0 %}active show{% endif %}" id="{{ b[1] }}" role="tabpanel" aria-labelledby="{{ b[1] }}-tab">{{ b[2] }}</div>
+      {% endfor %}
+    </div>
+    {% else %}
+    <p class="text-danger">Failed to generate the boilerplate</p>
+    {% endif %}
+</div>
+
+<script type="text/javascript">
+    function toggle(id) {
+        var element = document.getElementById(id);
+        if(element.style.display == 'block')
+            element.style.display = 'none';
+        else
+            element.style.display = 'block';
+    }
+</script>
+</body>
+</html>
\ No newline at end of file
diff --git a/nimare/tests/test_reports.py b/nimare/tests/test_reports.py
new file mode 100644
index 000000000..5d54badc0
--- /dev/null
+++ b/nimare/tests/test_reports.py
@@ -0,0 +1,39 @@
+"""Test nimare.reports."""
+import os.path as op
+
+import pytest
+
+from nimare import workflows
+from nimare.correct import FWECorrector
+from nimare.reports.base import run_reports
+
+
+@pytest.mark.parametrize(
+    "estimator,corrector,diagnostics",
+    [
+        ("ale", FWECorrector(method="montecarlo", n_iters=10), "jackknife"),
+        ("kda", "fdr", "focuscounter"),
+    ],
+)
+def test_reports_function_smoke(
+    tmp_path_factory,
+    testdata_cbma_full,
+    estimator,
+    corrector,
+    diagnostics,
+):
+    """Run smoke test for CBMA workflow."""
+    tmpdir = tmp_path_factory.mktemp("test_reports_function_smoke")
+    results = workflows.cbma_workflow(
+        testdata_cbma_full,
+        estimator=estimator,
+        corrector=corrector,
+        diagnostics=diagnostics,
+        output_dir=tmpdir,
+    )
+
+    run_reports(results, tmpdir)
+
+    filename = "report.html"
+    outpath = op.join(tmpdir, filename)
+    assert op.isfile(outpath)
diff --git a/nimare/tests/test_workflows.py b/nimare/tests/test_workflows.py
index 62ab91871..606cb2e69 100644
--- a/nimare/tests/test_workflows.py
+++ b/nimare/tests/test_workflows.py
@@ -103,7 +103,11 @@ def test_ale_workflow_cli_smoke_2(tmp_path_factory):
     ],
 )
 def test_cbma_workflow_function_smoke(
-    tmp_path_factory, testdata_cbma_full, estimator, corrector, diagnostics
+    tmp_path_factory,
+    testdata_cbma_full,
+    estimator,
+    corrector,
+    diagnostics,
 ):
     """Run smoke test for CBMA workflow."""
     tmpdir = tmp_path_factory.mktemp("test_cbma_workflow_function_smoke")
diff --git a/nimare/workflows/cbma.py b/nimare/workflows/cbma.py
index 1bac1dc05..ca4c9c473 100644
--- a/nimare/workflows/cbma.py
+++ b/nimare/workflows/cbma.py
@@ -1,4 +1,5 @@
 """Workflow for running an coordinates-based meta-analysis from a NiMARE database."""
+import copy
 import itertools
 import logging
 import os.path as op
@@ -102,7 +103,8 @@ def cbma_workflow(
     Returns
     -------
     :obj:`~nimare.results.MetaResult`
-        Results of Estimator and Corrector fitting with cluster and diagnostic tables.
+        Results of Estimator, Corrector, and Diagnostics fitting with label maps,
+        cluster and diagnostic tables.
     """
     n_cores = _check_ncores(n_cores)
 
@@ -154,14 +156,20 @@ def cbma_workflow(
     corr_results = corrector.transform(results)
 
     LGR.info("Generating clusters tables and performing diagnostics on corrected meta-analyses...")
+    # Perform diagnostic only on desc-mass when using montecarlo correction
+    corr_method = corr_results.get_params()["corrector__method"]
+    modalities = ["_desc-mass", "_corr-"] if corr_method == "montecarlo" else ["_corr-"]
     img_keys = [
         img_key
         for img_key in corr_results.maps.keys()
-        if img_key.startswith("z_") and ("_corr-" in img_key)
+        if img_key.startswith("z_") and all(mod in img_key for mod in modalities)
     ]
+
     for img_key, diagnostic in itertools.product(img_keys, diagnostics):
-        diagnostic.target_image = img_key
-        corr_results = diagnostic.transform(corr_results)
+        # Work on copy of diagnostic:
+        diagnostic_cp = copy.deepcopy(diagnostic)
+        diagnostic_cp = diagnostic_cp.set_params(target_image=img_key)
+        corr_results = diagnostic_cp.transform(corr_results)
 
     if output_dir is not None:
         LGR.info(f"Saving meta-analytic maps, tables and boilerplate to {output_dir}...")
diff --git a/setup.cfg b/setup.cfg
index 426b14eb4..f8f21dd92 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -40,15 +40,18 @@ python_requires = >= 3.8
 install_requires =
     cognitiveatlas  # nimare.annotate.cogat
     fuzzywuzzy  # nimare.annotate
+    jinja2 # nimare.reports
     joblib  # parallelization
     matplotlib>=3.3  # this is for nilearn, which doesn't include it in its reqs
     nibabel>=3.2.0  # I/O of niftis
     nilearn>=0.10.1
     numba>=0.57.0 # used by sparse
     numpy>=1.21
-    pandas>=1.1.5
+    pandas>=2.0.0
     patsy  # for cbmr
+    plotly  # nimare.reports
     pymare~=0.0.4rc2  # nimare.meta.ibma and stats
+    pyyaml # nimare.reports
     requests  # nimare.extract
     scikit-learn>=1.0.0  # nimare.annotate and nimare.decode
     scipy>=1.6.0
@@ -88,7 +91,7 @@ minimum =
     nibabel==3.2.0
     nilearn==0.10.1
     numpy==1.21
-    pandas==1.1.5
+    pandas==2.0.0
     pymare==0.0.4rc2
     scikit-learn==1.0.0
     scipy==1.6.0