The behavior of motorcyclists is one of the key determinants of traffic safety and the reduction of road accidents. Motorcycles are more at risk of accidents due to their specific characteristics, including the lack of adequate physical protection and the high mobility of drivers. A detailed analysis of the behavior of this group of road users, especially using well-known behavioral models such as the Theory of Planned Behavior (TPB) and the Motorcycle Rider Behavior Questionnaire (MRBQ), can help predict risky behaviors and improve safety policies. In addition, the use of computer simulations in the analysis of motorcyclist behavior allows for the examination of their reactions in controlled and diverse environments, which may not be possible in the real world for reasons of cost and safety. The main objective of the study is to provide a comprehensive framework for analyzing motorcycle rider behavior based on the Theory of Planned Behavior (TPB) and the Motorcycle Rider Behavior Questionnaire (MRBQ) and its application in traffic simulations. The research method is based on a literature review and selected studies are collected from reputable international databases. A review of previous studies shows that qualitative data from TPB and MRBQ can be converted into quantitative parameters using methods such as numerical scoring (Likert scale) and component weighting. When these parameters are integrated into traffic simulation models, it is possible to analyze different scenarios and predict the risk of motorcyclist behavior with higher accuracy.