Today, road accidents are one of the problems of transportation systems and are the most unfortunate one. This highlights the importance of planning to prevent it. In this regard, the present study investigates modeling and planning to predict road traffic accidents using logistic regression. In this research, after identifying the factors affecting accidents, we predict the accidents using logistic regression for road-climate and temporal factors and then we test the fitting of the regression model. The findings indicated that the role of the factors affecting on the accident is highly dependent on the presence of other factors in the accident modeling and the role of each factor on the occurrence of the accident varies. therefore, in interpreting the effect of different parameters on accident occurrence , we should be aware of the role of parameters dependence. therefore, in interpreting the effect of different parameters on accident occurrence , we should be aware of the role of parameters dependence. The overall accuracy of the model was 0.984 for road-climate parameters and 0.97 for time parameters, both of which showed excellent fit. Also The time factor also indirectly affects the occurrence of road accidents by changing the factors affecting the accidents at different intervals. As another results of this study, we can refer to the effect of different factors on accidents in different directions due to their different nature. Finally, it can be deduced that predicting road accidents based on different factors can be effective to take road safety corrective measures.