This research presents the results of a study on the behavior of international tourists who visit Chiang Mai province, Thailand. The aim is to create a predictive model of tourist types using data mining techniques. Two response categories are defined: cultural tourism and adventure tourism. It was found that attributes such as car rental usage, the number of travelers, travel characteristics, and gender influence the response. Additionally, the study presents the relationships between data, revealing interesting patterns. For instance, adventure tourists always use car rental services with a confidence level of 100%. Through the analysis of behavior and relationship rules, models for both types of tourists were developed using data grouping techniques, identifying unique attributes. For example, cultural tourists are typically aged between 35 and 44 years, while adventure tourists are typically aged between 25 and 34 years.