The objective of this study was to investigate factors influencing occurrence of pedestrian and bicycle crashes in Tennessee. Of interest were demographic and socio-economic, roadway geometry, traffic, and land use factors that could influence pedestrian crash rates on specific infrastructure. Geographic Information System (GIS) and statistical modeling were applied to study the crash patterns with respect to these factors. GIS was used to geo-locate and cluster the crash locations onto the roadway network, joined with background data of the crash locations. Negative Binomial (NB) regression was used to model the relationship between contributing factors and the crashes to detect any positive or negative correlations with the crashes. The following factors were found to have significant correlation with pedestrian and bicycle crash occurrences; percentage distribution of population by race, age groups, mean household income, percentage in the labor force, poverty level, and vehicle ownership. Land use, number of lanes crossed by pedestrians or bicyclists, posted speed limit and the presence of special speed zones, all were found to influence the occurrence of these crashes significantly. The findings were used to identify patterns of pedestrian and bicycle high crash locations in Tennessee and flagged combination of demographic, socioeconomic and geometry variables which if present are good indicators to TDOT as areas likely to experience pedestrian and bicycle crashes.