Utilizing a Criminal Event Perspective, the analyses of this dissertation test a variety of relationships to the dependent variable: the Criminal Lethality Index. Data from the National Incident-Based Reporting System, the Census and American Community Survey, the American Trauma Society, and data derived from the Census’s mapping TIGER files are combined to create a database of 190 cities. This database is used to test road network connectivity (Gama Index), medical resources, criminal covariates and Social Disorganization variables in relation to a city’s Criminal Lethality Index. OLS regression demonstrates a significant and negative relationship between a city’s Gama Index and its Criminal Lethality Index. In addition, percent male, percent black, median income and percent of the population employed in diagnosing and treating medical professions were all consistently positively related to Criminal Lethality. The percent of males 16 to 24, percent of single parent households, and Concentrated Disadvantage Index were all consistently and negatively related to Criminal Lethality. Given these surprising results, additional diagnostic regressions are run using more traditional dependent variables such as the number of murders in a city and the proportion of aggravated assaults with major injuries per 100,000 population. These reveal the idiosyncratic nature of utilizing the Criminal Lethality Index. This dependent variable has proven useful in some circumstances and counterintuitive in others. The source of the seemingly unintuitive results is the fact that certain factors only reduce murders but many factors impact both murder and aggravated assaults, thereby creating difficultly when trying to predict patterns in Criminal Lethality