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The Belgian railroad network is one of the most dense railroad networks of the world. Each day, more than 750,000 passengers travel by train to go to work, to school, on vacation or to make a trip. On peak moments, a huge flow of people has to get on and of the trains, enters or leaves the train station, and must find and a seat in the train itself. If the train company wants to promote train travelling, the quality must be higher and the occupancy must be tolerable for the passengers. In this thesis, the effects of occupancy will be researched in order to understand why a high occupancy disturbs the people on the train, and maybe prevents them from taking the train. To optimize train travelling, it would be nice that passengers can check how crowded the trains are before boarding them or planning their trip. Therefore, in the second part of this thesis, an investigation will be executed to see whether it is possible to predict the occupancy on trains based on data of the past. The data used to make the model is provided by iRail, an open-source train application.