Linear Regression is a predictive model used to learn the relationship between input variables and a target variable. The algorithm aims to find the optimal values for the slope (m) and y-intercept (b) of the equation y = mx + b, such that for any value of x, it can accurately predict the value of y. In this tutorial, we applied Linear Regression on house price prediction based on the area of the house. We also demonstrated how to improve the accuracy of the model by using multiple linear regression instead of simple linear regression. The multiple regression model showed a 211.8% increase in performance and a 66.67% decrease in margin of error compared to the simple model.