The incidence of deaths, injuries, and disability as a result of a road traffic crash is now a serious problem in Ethiopia. This study aimed at identifying significant patterns and major causes of road traffic crash using a data mining application. Secondary data were collected from different police offices in Dessie and its surroundings. In order to extract important patterns contributing to road traffic crash from the dataset collected by police officers, the study applied association rule mining. WEKA tool, a machinelearning software in Java, was adopted for undertaking the experiment. The findings of the study revealed that road traffic crash occurred by drivers’ of the age 21-26 years and driving experience less than or equal to 4 years, road geometric straight, light condition day and where the road type is asphalt, at most 3 peoples are killed or injured in good road condition and with no car defect in Dessie and its surroundings by road traffic crash. The major causes of road traffic crashes were not giving priority for pedestrians, over speeding, reckless, and not giving priority for other vehicles. The main factors contributing to the causes of road traffic crashes were related to drivers’ behavior (age, experience, and educational status) and road conditions. Cognizant of these findings, we recommend that changing the mindset of drivers, giving special attention while giving a driving license, having traffic lights, putting traffic signals on risk areas, and creating awareness about traffic rules and regulations by the concerned bodies needs special attention to mitigate road traffic crashes.