Loan Approval Prediction using ML

This project builds a machine learning model that predicts whether a loan application will be approved based on applicant details such as income, credit score, employment status, loan amount, and past repayment history.

The workflow includes data cleaning, feature engineering, handling missing values, training ML models like Logistic Regression or Decision Trees, and evaluating performance using accuracy and confusion matrix.

The model helps financial institutions automate loan screening and make data-driven decisions.