In this study, models will be introduced which are developed from historical UFC data and aim to predict the fight outcomes between mixed martial arts fighters within the UFC. The paper will explore multivariate linear probability regression analysis using variables which were provided and developed from a large dataset to effectively predict the probability of a fighter winning a given fight. It will analyze several multivariate regression models and compare, internally, the accuracy of each model and account for limitations within the models. Then, the model’s efficacy will be tested by recent UFC fights and adjusted to find a more accurate equation that maximizes profit in sports betting using implied probability from betting odds and comparing them to the model’s predicted probabilities.