Credit card Fraud has emerged as a bigger problem with an increase in online transactions and e-commerce. A credit card fraud happens when a fraudster uses your credit card information to make unauthorized purchases in your name. Credit card companies need to address these fraudulent transactions so that customers are not charged for the goods they did not buy. In this paper, we aim to tackle such fraudulent transactions by identifying them using various machine learning algorithms like Logistic Regression, Random Forest and, eXtreme Gradient Boosting. The results of the algorithms are based on accuracy, precision, recall, and F1-score. The algorithms are compared, and the algorithm that has the greatest accuracy, precision, recall, and F1-score is considered as the best algorithm that is used to detect fraudulent transactions.