This project predicts user personality types based on social behavior inputs using a Random Forest model. It covers data preprocessing, feature selection, model training, and evaluation, achieving 80% accuracy. The project demonstrates a complete machine learning pipeline, from data handling to deployment for reliable personality predictions.