Credit card fraud detection is the most frequently happening issue in the current world. This is because of the ascent in both online exchanges and web based business stages. Credit card fraud occurs for the most part happens when the card was taken for any of the unapproved purposes or in any event, when the fraudster utilizes the credit card data for his utilization. In the current world, we are confronting a great deal of these issues. To distinguish the fake exercises the credit card fraud detection discovery framework was presented. This project motto for focus on machine learning algorithm. The Algorithms utilized are decision tree Algorithms, KNN Algorithms, SVM Algorithms, Logistic regression Algorithms, Random forest Algorithms and the XGBoost Algorithms. The results of these Algorithms depend on accuracy, confusion matrix, and F1-score. XG Boost considered as the best algorithm that is used to detect the fraud.