As we are studying MS, we know the amount of pressure someone has to go through during MS admissions, there are different requirements for the admission process and after meeting them all one will get a chance into the MS course of a certain University and In this project, we have taken the dataset of graduate admissions and our goal is to find out some important features from this dataset through Explanatory Data Analysis (EDA) and then we applied machine learning classifiers on this data to observe which model best fits this data. We’ve applied five ML classifiers namely, Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and Naive Bayes. /Dept. of Applied Statistics, School of Applied Science and Technology, Maulana Abul Kalam Azad University of Technology, West Bengal, India. /Date of submission : 09/06/2022