This is my final year project which is related to credit scoring. We used ensemble learning classifiers like Random Forest Classifier Gradient Classifier, Logistic Regression, and Bagging to predict the credit score of a person. The least accuracy we got from model was up to 80%. The most accurate of these classifiers were gradient boosting and bagging, with an accuracy of up to 90%. The final model has been developed and deployed using Flask (micro-framework for backend web development in Python). It has a beautiful login and signup page. The database used is MYSQL. There is a video file attached in which I gave a demo of project.