The purpose of this study is to examine the efficiency of police departments in solving crime and consists of 61 police departments in the State of Texas, where the population exceeded 50,000 in year 2008. Data Envelopment Analysis is the methodology used to measure the relative efficiency of decision-making units (DMUs, i.e. police departments) by converting resources or inputs into outputs. Inputs used in the study were police department annual budget per capita, full-time equivalent police officer per 1,000 population, police personnel per 1,000 population, police vehicle per 1,000 population, and police officer education level. Outputs used included the crime rate and the crime clearance rate. Discretionary variables include police department budget, number of police vehicles, number of commissioned police officers, number of police department employees, and entry level education. Population density was the only control variable used in the study. A total of 21 models were fitted with various combinations of input and output variables. It was determined that three police departments were consistently efficient throughout all models: Beaumont, Cedar Park, and Harlingen, and two cities consistently scored in the lower quartile of inefficiency: Allen and Euless. A sensitivity analysis was conducted by removing the three efficient DMUs. Most of the models gained newly efficient DMUs in addition to the previous efficient DMUs that were not excluded from the analysis. Missouri City and Waco lie on the best practice frontier in all models. Crime is a continuing concern of both the general population and of policy makers. The existence of crime affects all populations, some more directly than others. It is also the concern of policy makers to address the problem of crime in a positive and aggressive manner by identifying initiatives that work and identifying and reducing inefficiencies in the business of solving crime. The focus of this study is the inefficiencies within police departments. By identifying inefficiencies, policy makers can make adjustments to police programs that increase effectiveness and lower costs. Appendices list inefficiencies and potential improvements model by model and city by city. The greatest sources of inefficiency are defined by the slacks in the results.