PURPOSES : As road pavement design in an apartment complex varies from one site to another, it is practically difficult to calculate and estimate the traffic volume of construction vehicles. Therefore, this study introduces a methodology to estimate the number of construction vehicles and use it as an indicator to evaluate the conditions of road pavement in an apartment complex. METHODS: Through a literature review and site survey, the operational status of the construction vehicles passing through the site was identified, and the factors affecting the number of construction vehicles were analyzed. The methodologies used to estimate the number of construction vehicles were verified by calculating the Cumulative Load Prediction Index (CLPI), which is a predictive index of the cumulative load on each path. By using this index, the traffic volume of construction vehicles can be estimated based on the number of households in an apartment complex. To prove this definition, we examined the surface and core conditions, and compared the results against the predicted values. RESULTS : By comparing the Cumulative Load Prediction Index with the crack rate on the pavement surface, we obtained a correlation coefficient of 0.92. Furthermore, the analysis indicated that the core condition rate would decrease as the Cumulative Load Prediction Index increased. This correlation between the Cumulative Load Prediction Index, and the pavement surface and core status demonstrates that the traffic volume can be estimated by considering the number of households. CONCLUSIONS: The Cumulative Load Prediction Index presented in this study is a suitable indicator for estimating the conditions of the road pavement in an apartment complex by considering the number of households in the complex, even if the construction processes and characteristics vary.