The key of the planning of public transport systems is the accurate prediction of the traffic load, or the correct execution of the planning stage assignment. This requires not only a well-functioning assignment method, but also reliable passenger data. Reliable passenger data means time-dependent origin-destination matrix. To solve the problem of lack of time-dependent passenger data we have developed a forecasting method. It consists of three stages. In the first stage we collect full scope cross-section data. This can be done either with personnel or an automatic counting system. If personnel are used it costs a lot and there are many possible errors. However the results in most cases are good enough. Automatic counting system can be either a counter machine or even a simple "Check in" E-ticketing system. In the second stage, we link boarding and alighting. As result we get the origin-destination matrix for each run. This method is based on the likelihood of alighting at a given stop. In the third stage, we combine origin-destination matrices of the runs through transfers. At this stage we assume that the probability of a transfer between two runs in a given stop is proportional to the travel possibilities in this relation. To view the entire method in the practice we proved it in a Hungarian cities. The results were reliable, so they could be use in the planning process. © 2012 IEEE.