Forensic entomology is a subdiscipline of entomology that involves the use of insect behavior and developmental data to aid in criminal investigations. Genetic data has become increasingly important to the field as there has been a push for DNA-based species identification methods of forensically relevant insects. Genetic data can also elucidate population structure and relatedness of these insects, and such knowledge can contribute to the development of more specific datasets for insects in different regions. The first study presented here investigated the phylogenetics of sister species Lucilia cuprina and Lucilia sericata to identify possible subspecies divisions and issues with DNA-based identifications in the United States. The initial aim of this study was to identify genetic differences between specimens of L. cuprina that preferred live versus carrion flesh. Flies collected from Indiana, USA and South Africa were sequenced and analyzed. Upon sequencing of the genes COI, Period, and 28s, our results indicated that L. cuprina from Indiana possess a unique combination of nuclear and mitochondrial haplotypes that suggest a unique lineage, possibly indicating modern hybridization with L. sericata. The inability of both nuclear and mitochondrial genes to distinguish between L. cuprina and L. sericata raises questions about the capabilities of DNA-based species identifications within this genus. Additionally, the inability of these genes to distinguish between specimens that preferred live versus carrion flesh highlights a need for continued research of these behavioral differences. The second study presented here investigated the population structure and relatedness of house flies in the American southwest in relation to a civil lawsuit where neighbors of a poultry farm alleged that flies were emanating from the farm to their homes. Musca domestica (house fly) specimens were collected from the chicken farm and from locations in varying directions and distances from the farm. Amplified fragment length polymorphism (AFLP) analysis was performed and the data were used in a number of analyses. Population reallocation simulations generally indicated that samples from different locations were not genetically different enough from other locations to allocate to their true origin population over others. Kinship analysis showed differences in samples collected in a later season that indicate a genetic bottleneck over time. Population structure analysis indicated the presence of two intermixing genetic populations in the dataset. AMOVA revealed that the majority of genetic variation laid within, rather than among, populations. A Mantel test revealed no significant correlation between genetic and geographic distances. These results indicate that the M. domestica population in this region of southwestern America is large and intermixing, with no clear genetic distinctions between specimens collected at the poultry farm versus the surrounding locations. In regard to the civil lawsuit, it was not possible to conclude that the flies did not emanate from the poultry farm. In a broader perspective, these data can be utilized to develop pest management strategies in this region. Overall, the data from both studies presented here will be useful to forensic investigations, development of more specific and detailed data and identification techniques, and pest control measures.