diff --git a/datafusion/core/tests/parquet/filter_pushdown.rs b/datafusion/core/tests/parquet/filter_pushdown.rs
index d337979e5fd00..2039e2a72b259 100644
--- a/datafusion/core/tests/parquet/filter_pushdown.rs
+++ b/datafusion/core/tests/parquet/filter_pushdown.rs
@@ -28,10 +28,19 @@
 
 use arrow::array::{ArrayRef, Int32Array, StringArray};
 use arrow::compute::concat_batches;
+use arrow::datatypes::SchemaRef;
 use arrow::error::ArrowError;
 use arrow::record_batch::RecordBatch;
+use datafusion::datasource::listing::PartitionedFile;
+use datafusion::datasource::object_store::ObjectStoreUrl;
+use datafusion::datasource::physical_plan::ParquetSource;
+use datafusion::datasource::source::DataSourceExec;
+use datafusion::physical_expr::expressions::col as physical_col;
+use datafusion::physical_expr::{LexOrdering, PhysicalSortExpr};
+use datafusion::physical_plan::filter::FilterExec;
 use datafusion::physical_plan::metrics::{MetricValue, MetricsSet};
-use datafusion::physical_plan::{collect, displayable};
+use datafusion::physical_plan::{ExecutionPlan, collect, displayable};
+use datafusion::physical_planner::DefaultPhysicalPlanner;
 use datafusion::prelude::{
     Expr, ParquetReadOptions, SessionContext, col, lit, lit_timestamp_nano,
 };
@@ -39,9 +48,12 @@ use datafusion::test_util::parquet::{ParquetScanOptions, TestParquetFile};
 use datafusion_expr::utils::{conjunction, disjunction, split_conjunction};
 use std::path::Path;
 
-use datafusion_common::DataFusionError;
 use datafusion_common::test_util::parquet_test_data;
+use datafusion_common::{DataFusionError, ToDFSchema};
+use datafusion_datasource::file_scan_config::FileScanConfigBuilder;
 use datafusion_execution::config::SessionConfig;
+use datafusion_physical_optimizer::PhysicalOptimizerRule;
+use datafusion_physical_optimizer::filter_pushdown::FilterPushdown;
 use itertools::Itertools;
 use parquet::arrow::ArrowWriter;
 use parquet::file::properties::WriterProperties;
@@ -62,6 +74,283 @@ async fn read_parquet_test_data<T: Into<String>>(path: T) -> Vec<RecordBatch> {
         .unwrap()
 }
 
+fn small_parquet_file(
+    tempdir: &TempDir,
+    schema: &SchemaRef,
+    name: &str,
+    row_groups: &[&[i32]],
+    row_group_size: Option<usize>,
+) -> TestParquetFile {
+    let mut properties = WriterProperties::builder();
+    if let Some(row_group_size) = row_group_size {
+        properties = properties.set_max_row_group_row_count(Some(row_group_size));
+    }
+    TestParquetFile::try_new(
+        tempdir.path().join(name),
+        properties.build(),
+        row_groups.iter().map(|values| {
+            RecordBatch::try_new(
+                Arc::clone(schema),
+                vec![Arc::new(Int32Array::from(values.to_vec())) as ArrayRef],
+            )
+            .unwrap()
+        }),
+    )
+    .unwrap()
+}
+
+fn ordered_scan_with_fetch(
+    file: &TestParquetFile,
+    schema: &SchemaRef,
+    source: ParquetSource,
+    fetch: Option<usize>,
+) -> Arc<dyn ExecutionPlan> {
+    let path = file.path().canonicalize().unwrap();
+    let ordering = LexOrdering::new(vec![
+        PhysicalSortExpr::new_default(physical_col("a", schema).unwrap()).asc(),
+    ])
+    .unwrap();
+    let config =
+        FileScanConfigBuilder::new(ObjectStoreUrl::local_filesystem(), Arc::new(source))
+            .with_file(PartitionedFile::new(
+                path.to_string_lossy(),
+                path.metadata().unwrap().len(),
+            ))
+            .with_limit(fetch)
+            .with_output_ordering(vec![ordering])
+            .build();
+    DataSourceExec::from_data_source(config)
+}
+
+fn physical_predicate(
+    ctx: &SessionContext,
+    schema: &SchemaRef,
+    value: i32,
+) -> Arc<dyn datafusion::physical_expr::PhysicalExpr> {
+    ctx.create_physical_expr(
+        col("a").eq(lit(value)),
+        &Arc::clone(schema).to_dfschema().unwrap(),
+    )
+    .unwrap()
+}
+
+async fn int_values(plan: Arc<dyn ExecutionPlan>, ctx: &SessionContext) -> Vec<i32> {
+    collect(plan, ctx.task_ctx())
+        .await
+        .unwrap()
+        .into_iter()
+        .flat_map(|batch| {
+            batch
+                .column(0)
+                .as_any()
+                .downcast_ref::<Int32Array>()
+                .unwrap()
+                .values()
+                .iter()
+                .copied()
+                .collect::<Vec<_>>()
+        })
+        .collect()
+}
+
+#[tokio::test]
+async fn filter_pushdown_preserves_fetch_with_row_filtering() {
+    let schema = Arc::new(arrow::datatypes::Schema::new(vec![
+        arrow::datatypes::Field::new("a", arrow::datatypes::DataType::Int32, false),
+    ]));
+    let tempdir = TempDir::new_in(Path::new(".")).unwrap();
+    // One row group makes this a row-filtering regression, not a pruning one.
+    let file =
+        small_parquet_file(&tempdir, &schema, "one_group.parquet", &[&[0, 1]], None);
+    let mut config = SessionConfig::new()
+        .with_target_partitions(1)
+        .with_parquet_pruning(false);
+    config.options_mut().execution.parquet.pushdown_filters = true;
+    let ctx = SessionContext::new_with_config(config);
+
+    let original: Arc<dyn ExecutionPlan> = Arc::new(
+        FilterExec::try_new(
+            physical_predicate(&ctx, &schema, 1),
+            ordered_scan_with_fetch(
+                &file,
+                &schema,
+                ParquetSource::new(Arc::clone(&schema)).with_pushdown_filters(true),
+                Some(1),
+            ),
+        )
+        .unwrap(),
+    );
+    assert_eq!(
+        int_values(Arc::clone(&original), &ctx).await,
+        Vec::<i32>::new()
+    );
+
+    let zero_fetch: Arc<dyn ExecutionPlan> = Arc::new(
+        FilterExec::try_new(
+            physical_predicate(&ctx, &schema, 1),
+            ordered_scan_with_fetch(
+                &file,
+                &schema,
+                ParquetSource::new(Arc::clone(&schema)).with_pushdown_filters(true),
+                Some(0),
+            ),
+        )
+        .unwrap(),
+    );
+    assert_eq!(
+        int_values(Arc::clone(&zero_fetch), &ctx).await,
+        Vec::<i32>::new()
+    );
+    let zero_pushed = FilterPushdown::new()
+        .optimize(zero_fetch, ctx.state().config_options())
+        .unwrap();
+    assert_eq!(
+        int_values(Arc::clone(&zero_pushed), &ctx).await,
+        Vec::<i32>::new()
+    );
+    let zero_plan = displayable(zero_pushed.as_ref()).indent(false).to_string();
+    assert!(
+        zero_plan.contains("FilterExec") && !zero_plan.contains("predicate="),
+        "{zero_plan}"
+    );
+
+    let pushed = FilterPushdown::new()
+        .optimize(Arc::clone(&original), ctx.state().config_options())
+        .unwrap();
+    assert_eq!(
+        int_values(Arc::clone(&pushed), &ctx).await,
+        Vec::<i32>::new()
+    );
+    let plan = displayable(pushed.as_ref()).indent(false).to_string();
+    assert!(
+        plan.contains("FilterExec") && !plan.contains("predicate="),
+        "{plan}"
+    );
+
+    let planner = DefaultPhysicalPlanner::default();
+    let once = planner
+        .optimize_physical_plan(Arc::clone(&original), &ctx.state(), |_, _| {})
+        .unwrap();
+    assert_eq!(int_values(Arc::clone(&once), &ctx).await, Vec::<i32>::new());
+    let twice = planner
+        .optimize_physical_plan(once, &ctx.state(), |_, _| {})
+        .unwrap();
+    assert_eq!(int_values(twice, &ctx).await, Vec::<i32>::new());
+
+    let uncapped: Arc<dyn ExecutionPlan> = Arc::new(
+        FilterExec::try_new(
+            physical_predicate(&ctx, &schema, 1),
+            ordered_scan_with_fetch(
+                &file,
+                &schema,
+                ParquetSource::new(Arc::clone(&schema)),
+                None,
+            ),
+        )
+        .unwrap(),
+    );
+    let pushed = FilterPushdown::new()
+        .optimize(uncapped, ctx.state().config_options())
+        .unwrap();
+    assert_eq!(int_values(Arc::clone(&pushed), &ctx).await, vec![1]);
+    let plan = displayable(pushed.as_ref()).indent(false).to_string();
+    assert!(
+        !plan.contains("FilterExec") && plan.contains("predicate=a@0 = 1"),
+        "{plan}"
+    );
+}
+
+#[tokio::test]
+async fn filter_pushdown_preserves_fetch_with_pruning() {
+    let schema = Arc::new(arrow::datatypes::Schema::new(vec![
+        arrow::datatypes::Field::new("a", arrow::datatypes::DataType::Int32, false),
+    ]));
+    let tempdir = TempDir::new_in(Path::new(".")).unwrap();
+    // Separate row groups let statistics pruning change the row admitted by fetch.
+    let pruning_file = small_parquet_file(
+        &tempdir,
+        &schema,
+        "two_groups.parquet",
+        &[&[0], &[1]],
+        Some(1),
+    );
+    let ctx = SessionContext::new_with_config(
+        SessionConfig::new()
+            .with_target_partitions(1)
+            .with_parquet_pruning(true),
+    );
+
+    let original: Arc<dyn ExecutionPlan> = Arc::new(
+        FilterExec::try_new(
+            physical_predicate(&ctx, &schema, 1),
+            ordered_scan_with_fetch(
+                &pruning_file,
+                &schema,
+                ParquetSource::new(Arc::clone(&schema)).with_pushdown_filters(false),
+                Some(1),
+            ),
+        )
+        .unwrap(),
+    );
+    assert_eq!(
+        int_values(Arc::clone(&original), &ctx).await,
+        Vec::<i32>::new()
+    );
+    let pushed = FilterPushdown::new()
+        .optimize(Arc::clone(&original), ctx.state().config_options())
+        .unwrap();
+    assert_eq!(
+        int_values(Arc::clone(&pushed), &ctx).await,
+        Vec::<i32>::new()
+    );
+    let plan = displayable(pushed.as_ref()).indent(false).to_string();
+    assert!(
+        plan.contains("FilterExec") && !plan.contains("predicate="),
+        "{plan}"
+    );
+
+    let internal_file = small_parquet_file(
+        &tempdir,
+        &schema,
+        "internal.parquet",
+        &[&[0], &[1], &[2]],
+        Some(1),
+    );
+    let internal_predicate = ctx
+        .create_physical_expr(
+            col("a").gt_eq(lit(1_i32)),
+            &Arc::clone(&schema).to_dfschema().unwrap(),
+        )
+        .unwrap();
+    let internal_scan = ordered_scan_with_fetch(
+        &internal_file,
+        &schema,
+        ParquetSource::new(Arc::clone(&schema))
+            .with_pushdown_filters(false)
+            .with_predicate(internal_predicate),
+        Some(1),
+    );
+    assert_eq!(int_values(Arc::clone(&internal_scan), &ctx).await, vec![1]);
+    let original: Arc<dyn ExecutionPlan> = Arc::new(
+        FilterExec::try_new(physical_predicate(&ctx, &schema, 2), internal_scan).unwrap(),
+    );
+    assert_eq!(
+        int_values(Arc::clone(&original), &ctx).await,
+        Vec::<i32>::new()
+    );
+    let pushed = FilterPushdown::new()
+        .optimize(original, ctx.state().config_options())
+        .unwrap();
+    assert_eq!(
+        int_values(Arc::clone(&pushed), &ctx).await,
+        Vec::<i32>::new()
+    );
+    let plan = displayable(pushed.as_ref()).indent(false).to_string();
+    assert!(plan.contains("FilterExec"), "{plan}");
+    assert!(plan.contains("predicate=a@0 >= 1"), "{plan}");
+    assert!(!plan.contains("predicate=a@0 = 2"), "{plan}");
+}
+
 #[tokio::test]
 async fn single_file() {
     let batches =
diff --git a/datafusion/datasource/src/file_scan_config/mod.rs b/datafusion/datasource/src/file_scan_config/mod.rs
index 4e72b5e83bd23..6fbc0c2192209 100644
--- a/datafusion/datasource/src/file_scan_config/mod.rs
+++ b/datafusion/datasource/src/file_scan_config/mod.rs
@@ -62,7 +62,7 @@ use datafusion_physical_plan::execution_plan::SchedulingType;
 use datafusion_physical_plan::{
     DisplayAs, DisplayFormatType,
     display::{ProjectSchemaDisplay, display_orderings},
-    filter_pushdown::FilterPushdownPropagation,
+    filter_pushdown::{FilterPushdownPropagation, PushedDown},
     metrics::ExecutionPlanMetricsSet,
 };
 use log::{debug, warn};
@@ -1028,6 +1028,13 @@ impl DataSource for FileScanConfig {
         filters: Vec<Arc<dyn PhysicalExpr>>,
         config: &ConfigOptions,
     ) -> Result<FilterPushdownPropagation<Arc<dyn DataSource>>> {
+        // A new filter or pruning predicate can change which rows reach the enforced scan cap.
+        if self.limit.is_some() {
+            return Ok(FilterPushdownPropagation::with_parent_pushdown_result(
+                vec![PushedDown::No; filters.len()],
+            ));
+        }
+
         // Remap filter Column indices to match the table schema (file + partition columns).
         // This is necessary because filters refer to the output schema of this `DataSource`
         // (e.g., after projection pushdown has been applied) and need to be remapped to the table schema