Rainfall Prediction is the application of science and technology to predict the state of the atmosphere. The purpose of predicting rainfall is to make use of water resources, crop productivity and pre-planning of water structures. Artificial neural network have been applied to compute the real-time rainfall prediction. The main problem with artificial neural network is, it takes much time to train the network. It does not specify the rule for determining structure. In proposed system, we used regression and classification algorithms under the supervised learning. Inspired by machine learning, a desired techniques viz., linear regression, multiple linear regression, logistic regression, support vector machine, naïve bayes algorithm are used in the proposed system. The parameters of the proposed system are mean square error (MSE), root mean square root(RMSE) and coefficient of determination(r2). The prediction of the proposed system is done by comparative analysis of these parameters. Based on the results, the best algorithm should be declared for rainfall prediction.