In this paper we mainly focus on credit card fraud detection in real world. Here the credit card fraud detection is based on fraudulent transactions. Generally, credit card fraud activities can happen in both online and offline. But in today's world online fraud transaction activities are increasing day by day. So,to find the online fraud transactions various methods have been used in existing system. In proposed system we use random forest algorithm(RFA) for finding the fraudulent transactions and the accuracy of those transactions. This algorithm is based on supervised learning algorithm where it uses decision trees for classification of the dataset. After class ification of dataset a confusion matrix is obtained. The performance of RFA is evaluated based on the confusion matrix.