This thesis seeks to develop a comprehensive understanding of chronically underused stations throughout the Chicago Transit Authority’s rail network. I will specifically focus on land use, demographic, and built environment indicators within block groups at a half-mile radius as independent variables, studying these variables with all rail stations in the CTA system from 2016-2019. Through the use of negative binomial multivariate regression models with American Community Survey (ACS) block-group level and City of Chicago Zoning Ordinance data, I seek to discern common trends shaping the current status of the system’s use with a distinct focus on the large variety of ridership quantities in the system. Results show that demographic indicators of white population and employment, were significantly correlated with heightened ridership at a system-wide level. Significant zoning types offer unique contributions to ridership assumptions, as Downtown Core (DC), Private Development (PD), and Residential Single-Unit (RS) districts see estimated increased ridership proportional to their areas proximate to stations; the areas of Transit (T) and Neighborhood Commercial (C1) districts show negative estimates. Finally, the model suggests highly significant positive coefficients buildings finished within the eras of post-2000 and 1940-1969. Despite the existence of multiple significant regressors among each type of presumed transit effectors, high standard errors deter certainty of conclusions in each highly significant variable in the final model, which uses 35 unique regressors. This analysis should not be interpreted causally, but the recognition of significant zoning, demographic, and built environment coefficients in a suggest intricate relations to ridership at the system-wide level.