In this project we aim to use mathematical and computational modeling to identify factors influencing the distribution of arrests in the Los Angeles region. To accomplish this goal, we are creating agent based simulations of police activity and arrest patterns. We plan to vary the probability of arrest and the police-agent path parameters in order to generate different arrest distributions. We will compare our model outputs to recent LAPD arrest data with the aim of identifying factors that contribute to LA’s arrest distributions. These factors will include demographic data along with police-agent patrol patterns. We anticipate this comparison will lead to a better understanding of LAPD arrests and correlating factors that we can use in related future work.