This research aims to understand how Commute Trip Reduction (CTR) transit subsidy programs, when controlling for various built environment variables and the structure of the transit network, impact the number of trips individual employees of large employers in the Central Puget Sound region take commuting from their worksite. This transit utilization is measured using the ORCA fare card records over two nine week periods in 2015 and 2016. Manipulating monetary costs is a known method of transportation demand management. Earlier preliminary research has suggested that these transit subsidies do have a signicant impact on transit utilization. However, results in the wider literature suggest that transit utilization was operationalized in a way—defined on the level of an individual card without accounting for the existence of people who never take transit—that may have altered the infence of control variables. Indeed, some of the results were counterintuitive. In this research I attempt to avoid this by focusing solely on trips of employees of large employers to and from their worksites. This allows me to deduce how many employees are not utilizing transit and add them to the dataset. I then create a regression tree model that predicts the number of trips taken to and from an employer worksite on an individual card. The features of the model include subsidy values associated with each card, the closeness centrality of the stops around worksites weighted for travel time and headways— a measure designed to reflect the quality of transit service to that employer site—and the existence of employer provided parking. I find that higher centrality of worksites and higher pass subsidies both increase transit utilization while the existence of parking provided by the employer, whether free or paid, depresses transit utilization.