House price increases gradually, that is why there is a need to create such a system for prediction of house prices. This prediction will help developers knowing the selling price of a house. It will also assist customers to know about which is the perfect time to buy a flat. In this paper, we are going to predict the selling price of various houses. Selling prices are determined by various factors such as the location of the house, area of the property, the inflation rate of the current year, Apartment type, month and year of which we want to know the particular price. We are implementing various machine learning algorithms for building a predictive model for houses. We have considered housing data of 2000 properties. In this paper, We will be comparing the algorithms on the basis of parameters such as MAE, RMSE, MSE, accuracy.