Aim: To enhance the accuracy in predicting the house prices using Novel Linear Regression and Random Forest. Materials and Methods: This study contains 2 groups i.e Novel Linear Regression (LR) and Random Forest (RF). Each group consists of a sample size of 6 and G power software is used to determine sample size with pretest power value 0.8 and alpha is 0.05. Results: The Novel Linear Regression (LR) is 82% which is more accurate than Random Forest (RF) of 76.14% in classifying House Price Prediction with p = 0.7. Conclusion: The Novel Linear Regression(LR) model is significantly better than Random Forest (RF) in predicting House Price.