Freight transportation is an important factor in Turkish economic growth, and the high volume of truck traffic has increased traffic accidents on Turkish roads. However, to the best of our knowledge, no studies have investigated the factors that contribute to truck accidents. This study aims to reduce truck accident involvement and quantify the effect of variables on the occurrence of truck accidents on divided multilane interurban roads in Turkey. This study documents the performance of Poisson, Negative Binomial (NB), and Zero-inflated Negative Binomial Regression (ZINB) models to establish the relation between truck accidents and traffic and geometric road characteristics on a 282 km section of the Ankara-Aksaray-Eregli divided multilane interurban road. Model coefficients were estimated by the maximum likelihood method, and deviance and the Akaike information criterion were considered as goodness of fit statistics. The Vuong test was used to determine the appropriateness of using the ZINB model rather than the NB model. The results show that the NB model fitted the data very well. The proposed model for Turkish divided multilane interurban roads with a high percentage of truck traffic might be useful to detect critical factors and reduce truck accident involvement.