Public transit agencies often struggle with service reliability issues; when a train or bus does not arrive on time, passengers become frustrated and may be less likely to choose transit for future trips. To address reliability issues, transit authorities increasingly provide real-time information (RTI) to riders via countdown clocks in stations and passengers’ mobile devices. Though these new information technologies are now available in many transit systems throughout the country, their impact on overall transit ridership - particularly train ridership - remains unclear. Therefore, the objective of this research is to quantify the impact that providing RTI has on aggregate train ridership. The proposed method is an empirical evaluation of the New York City subway, which is the setting of a natural experiment in which some subway lines currently provide RTI to riders (e.g., 1/2/3, 4/5/6) whereas other subway lines do not (e.g., A/C/E, B/D/F/M). Regression analysis will be used to estimate the effect of RTI on subway ridership while controlling for other factors that affect ridership, such as weather, macroeconomic conditions (e.g., unemployment), and subway service (e.g., frequency). The results of this research are anticipated to have immediate implications for the MTA’s capital program because significant investments are needed to provide RTI on the remaining subway lines. Moreover, the findings will be critical to decision-makers at other transit operators who face pressure to increase ridership under limited budgets, particularly as they seek to prioritize investments in infrastructure, service offerings, and new technologies.