The modeling of average waiting time for transit passengers has an important role in public transport network coordination optimization and benefit analysis of public transportation system. The primary objective of this paper is to develop a mathematical model based on the statistical analysis of collected data to calculate the average waiting time for passengers to transfer from rail transit to buses. As an important part in modeling the average waiting time, the passenger arrival rate distributions are first studied. Since different transfer behaviors lead to different arrival rate distributions, the paper categorizes passengers transferring from rail transit to buses into two groups, namely direct transfer passengers and non-direct transfer passengers. Then, data of passenger arrival times, arrival and departure time for buses and rail cars are collected from a passenger survey at bus stops with transferring passengers in Beijing, which are used to analyze the passenger arrival rate distributions. It is shown that the lognormal distribution has the best fitting for direct transfer passengers, and the gamma distribution has the best fitting for non-direct transfer passengers. Subsequently, an average waiting time model for transferring passengers is developed based on the passengers arrival rate distributions. Further, case studies are conducted for two scenarios: with known real data and without real data. The results calculated using the proposed model are compared with the field collected data, resulting in relative errors of -3.69%, and -3.77% for two scenarios respectively. Finally, field collected data are used to analyze the impacts of the bus headway (bus arrival intervals for stop station), the headway of rail cars, and the proportion of direct transfer passengers on the average waiting time. The results could provide a decision guidance in practice for the operational control and management of urban transit systems.