Flood is one of the unfavorable natural disasters. This advancement of the flood prediction system provides cost-effective solutions and better performance. In this project, a prediction model is constructed using rainfall data to predict the occurrence of floods due to rainfall. The model predicts whether “flood may happen or not” based on the rainfall range for particular locations. Indian district rainfall data is used to build the prediction model. Machine learning methods are widely used in building an efficient prediction model for weather forecasting. This advancement of the prediction system provides cost-effective solutions and better performance. The dataset is trained with various algorithms like Random Forest Regression, Linear Regression, Lasso Regression, Support Vector Machine and Multilayer Perceptron. Among this, Lasso Regression algorithm performed efficiently with the highest accuracy of 89.40%. The LR flood prediction model can be useful for the climate scientist to predict the flood during a heavy downpour with the highest accuracy.