Big Data has often been used in the sports world. Especially in baseball, more and more general managers turn to pure statistics for team decisions. This paper attempts to use known batting statistics to predict how the same player will perform the following year. This information would help teams realize the true value of a player and decide whether they want them on the team or not. Our system uses data from Lehman’s Baseball collection to abstract notable features and use them as inputs to predict future batting average. All players were classified as positive or negative, meaning they will improve or worsen. Our models could then predict their class with around 65% accuracy, proving a correlation in our data.