Abstract: Road traffic accidents are a concrete manifestation of road traffic safety levels. In the current traffic accident prediction work, there is an insufficient mining of the time series relationship in the data, the predicted time period is too macroscopic, and the influencing factors related to traffic accidents are missing. Aiming at the above problems, a gradient boosted regression tree (GBRT) traffic accident model based on time series relationship is proposed. The model predicts the number of daily traffic accidents, deaths, and the number of vehicles involved in Leicester, England, from 2005 to 2015. Experimental results show that adding the time series relationship helps to improve the prediction accuracy of the model. The prediction results serve as a reference for the decision-making of the traffic management department. The modeling method brings positive reference significance to the modeling work of the same type of prediction problems.