Both models, linear and logistic, are only approximations to the true unknown population of data points. While the multiple linear model is easier to interpret and use, the logistical model captures the nonlinear nature of the population. There is no clear answer when it comes to selecting the correct model as the dataset used in the project may be lacking in key features, specifically financial variables. This lack of variables may have given the multiple linear model a better score. Overall, based on the data collected, the logistical regression is far better, statistically, than the multiple linear model.