Financial organisations and customers share a common fear about credit card fraud. Credit card fraud generally happens when the card was stolen for any of the unauthorized purposes or even when the fraudster uses the credit card information for his use. As a solution to this problem, machine learning algorithms have been developed to quickly identify and assist with fraudulent transactions. We want to use machine literacy styles to produce a model for detecting credit card fraud in this design. The design must be completed by obtaining sale data from the credit card firm, pre-processing the data to eliminate missing values and unnecessary data, and choosing crucial attributes to train the machine literacy model. The model will be trained with a range of machine learning methods, including logistic regression, SVM. Among the performance metrics that will be used to judge the model's effectiveness are perfection, recall, and best position. By altering the model's characteristics and parameters, performance will be improved as well.