Data mining is the process of examining large datasets to predict outcomes. Classification algorithms comes under supervised learning concept. In classification a set of data is categorized into classes. There are various Classification algorithms. Random Forest and Decision Tree are the two classification algorithms used in this paper. The classification results of these algorithms are compared in this study. The comparative study shows that Random Forest algorithm gives high accuracy than Decision Tree algorithm. These algorithms are measured by precision, recall, f-measures and kappa statistics. The performance of classification algorithms is studied using R statistical tool.