Aim: The main aim of this research study is to get the error free and accurate stock prices using novel approaches of linear regression and comparing it with Artificial neural networks. Materials and Methods: In this research study Linear regression algorithm is being compared with Artificial neural network algorithm for estimating Stock market values and error free values, which helps the users for availing the profits by estimating the previous sales by analyzing it through defining the set of modules . Sample size is determined by using the G power calculator and found to be 158 per group. Total of 2 groups are used. Results: Based on the analysis done Linear regression algorithm method has an accuracy of 85% and Artificial neural network has 73% and the significance value achieved is 1.000 (p>0.05). It shows that two groups are statistically insignificant. Conclusion: In this research study, the proposed Linear regression algorithm has shown the highly predicted values when compared to the Artificial neural network.