Abstract: Electric load forecasting or future electric load prediction is necessary in both domestic as well as industrial sectors. Since electric energy cannot be stored, it is necessary to predict the future electric load in every sector. If the load forecasting is incorrect on the transmission side, a high load current may travel through the conductors, potentially damaging them. The increased loads result in more current flowing through the conductors and ultimately through the equipment, load forecasting is also important in the distribution system. In this work, the techniques of linear regression and random forest regressor have been used for future load prediction. The main purpose of this work is to determine the best regression algorithm for future load prediction with reduced error among both linear regression and random forest regressor. A front end form is also developed to determine the future load.