Aim: To improve the accuracy in House Price Prediction using Novel Linear Regression and Ridge Regression. Materials and Methods: This study contains 2 groups i.e Novel Linear Regression and Ridge Regression. Each group consists of a sample size of 10 and the study parameters include alpha value 0.05, beta value 0.2, and the Gpower value 0.8. Results: The Novel Linear Regression achieved accuracy (91.79) better than the Ridge Regression accuracy (91.34%) in House Price Prediction. The statistical significance difference (two-tailed) is 0.01 (p<0.05). Conclusion: The Novel Linear Regression model is significantly better than the Ridge Regression in House Price Prediction. It can be also considered as a better option for the House Price Prediction.