This project employs machine learning models like Boosting, Random Forest, Naive Bayes, to predict travel insurance purchases. Analyzing demographic and behavioral data, the models balance accuracy and sales opportunity by considering classification error costs. The project delivers detailed insights and recommendations, aligning with the company's goals and risk tolerance