In 2015 bike-sharing has become a viable transportation mode in the urban core of many large cities worldwide. Notably lacking is research on the bike-sharing/transit connection. Bike-sharing provides an excellent solution to the “first-last mile” problem experienced by transit networks but data is difficult to collect due to the independent operation of each network. This thesis proposes an optimization algorithm of user mode choice based on minimizing cost. Required system characteristics for this optimization program are at least two bike-sharing market areas, transit links between the areas and a realistic potential for the vehicle network to become congested. The results show the optimal mode choice by Origin-Destination (OD) pair. This model was applied to trips from downtown Pasadena to downtown Los Angeles in California. These two areas are expected to have a bike-sharing system as soon as 2016 operated by the Los Angeles County Metropolitan Transportation Authority (METRO). Based on congestion from 1x to 4.25x the free-flow time, bike-sharing provides increasing value to commuters between these two areas. The simple parameters of this application including value-of-time and cost of use could be easily updated to reflect a deeper consideration of user cost.