Regression techniques like linear and polynomial regression are used to analyze data and predict outcomes for profits. The main goal of this paper is to discuss how these techniques work and how they are related. By finding correlations between variables, these methods help us understand how one variable changes in relation to another. They are useful for forecasting trends in data and can be used to predict future outcomes. The size and type of the dataset, as well as factors like quality and accuracy, affect the performance of these techniques. By understanding the relationship between linear and polynomial regression, new researchers can develop innovative approaches for improvement.