To solve the problem of flatness prediction of cement pavement in seasonal frozen region, the international roughness index (IRI) prediction revised model of cement pavement in frozen season was constructed using MEPDG. The model takes into account the traffic conditions, climatic conditions, and the characteristics of the materials of the pavement layers. The trends of CRK, TFAULT, SPALL, and SF were analyzed and verified with IRI correlation on the basis of the original prediction model. SPSS analysis software was used to obtain the prediction revised model of cement pavement roughness index in seasonal frozen region. The cement pavement survey data of Heilongjiang Province was used to verify this model. The results show that climate, traffic, and material parameters had significant influence on the four indexes CRK, TFAULT, SPALL, and SF. These indicators and international flatness index were linearly fitted with high reliability. The number of traffic, precipitation, rainfall, wet days, the number of freeze-thaw cycles, and the performance of pavement materials can be used to predict the international flatness index of cement pavement in seasonal frozen region. The accuracy of the model was high, with good practicability and high predictive performance.