Accurate prediction of serviceability is crucial in selecting the appropriate maintenance strategies for pavement management systems. Pavement Condition Index (PCI) measures the serviceability levels of pavements based on distresses. In general, the reduction in serviceability can be majorly attributed to traffic, environmental factors, and material properties. This study aimed to develop a comprehensive deterioration model incorporating various factors contributing to pavement conditions. A total of 97 pavement sections were filtered from Long-Term Pavement Performance (LTPP) database that covered 19 pavement distresses, such as rutting, fatigue cracking, block cracking, longitudinal cracking, transverse cracking, patching, potholes, etc. The deterioration model was established that help estimate the pavement conditions as a function of structural capacity of pavement, and environmental and climatic conditions. Two regression coefficients, which were part of deterioration model, were further correlated with traffic, structural condition of pavement, and climatic conditions. Furthermore, the accuracy of the deterioration model was measured using R2 = 0.75 and Se/Sy = 0.05 which indicates a good correlation between the observed PCI obtained from distress condition and predicted PCI from the deterioration model. In summary, this model can be effectively used to estimate the residual life in terms of PCI.