Transportation inequality poses significant challenges in car-dependent cities in the US, especially for Transit-Dependent Populations (TDPs) who rely on public transportation to meet their travel requirements. Research indicates that despite the rapid growth of ride-hailing services like Uber, TDPs primarily depend on conventional transit options such as buses and metros. This study differentiates between two classifications of ride-hailing services: Private Ride-hailing (PRH), represented by platforms like Uber and Lyft, where individuals hire and pay for their rides, occasionally sharing the journey with guests; and ride-sharing (RS), like UberPool, which allows users to divide travel expenses. However, a more profound comprehension is necessary to clarify why TDPs show a preference for one mode of transportation over another and the factors that influence their decision-making. This study utilises Structural Equation Modelling (SEM) to examine the direct and indirect relationships between explanatory and outcome variables, while investigating modal preferences and usage frequency in 48 densely populated urban areas in the US (N = 384). TDPs choose to use transportation services like Uber because of their effectiveness in reducing both travel and waiting time, in contrast to traditional Fixed-Route Transit Services (FRTS), which are relatively less efficient. TDPs’ inclination towards PRH leads to a greater dependence on ride-hailing services, whereas a preference for FRTS reduces this dependence. Significantly, the study demonstrates that TDPs’ modal preferences are not only influenced by their socioeconomic status or rational decision-making, but also by the complex interaction between these factors. These findings provide valuable information for policymakers who want to evaluate the sustainability of ride-hailing services for TDPs and effectively tackle transportation inequalities.