The aim of this experiment is to compare the performance of Linear Regression, Lasso Regression, and Ridge Regression to determine the most effective approach for predictive accuracy. The experiment evaluates each model using key error metrics and examines how L1 (Lasso) and L2 (Ridge) regularization influence accuracy, model stability, and coefficient behavior to identify the most reliable predictive approach.