PURPOSES : This study was conducted to develop a traffic accident prediction model using traffic accident data and management and service evaluation data on bus companies in Busan, and to determine the possibility of establishing customized traffic accident prevention measures for each company. METHODS: First, we collected basic data on the characteristics of urban bus traffic accidents and conducted basic statistical analysis. Then, we developed traffic accident prediction models using Poisson regression and negative binomial regression to examine the characteristics of major items of management and service evaluation affecting traffic accidents. RESULTS : The Poisson regression model showed overdispersion; hence, the negative binomial regression model was selected. The results of the traffic accident prediction model developed using negative binomial regression are acceptable at 95% confidence level (a = 0.05). CONCLUSIONS : The traffic accident prediction model indicates that the management of the traffic record system and internal and external management items in service evaluation have a significant effect on the reduction of traffic accidents. In particular, because human factors are the main cause of traffic accidents, bus traffic accidents are expected to greatly decrease if drivers' dangerous driving behaviors are effectively controlled by bus companies.