PURPOSES : This study aimed to estimate road pavement life expectancy using Bayesian Markov Mixture Hazard Model, to support infrastructure asset management. In addition, the life expectancies for the pavement condition index were compared among regional construction and management administrations. METHODS : Eleven years of National Highway road pavement monitoring data fused with ESAL (Equivalent Single Axle Loads), SNP (Structural Number of Pavement, an indicator of structural capacity), and average low temperature, total rainfall, and de-icing were used for the deterioration modeling. Deterioration modeling was performed through the Bayesian Markov Mixture Hazard Model. RESULTS : The expected life expectancy of the crack was estimated at 12.28 to 18.51 years, rut depth was estimated at 15.93 to 25.3 years, and the International Roughness Index was estimated at 10.44 to 14.33 years. It was also confirmed that the heterogeneity factor proposed in the Bayesian Markov Mixture Hazard Model could be used to analyze group characteristics and differences in the benchmark. CONCLUSIONS: This study provided important information in that it compared the life expectancies and structural characteristics of the pavement condition indexes among regional construction and management administrations. Based on this result, it is expected that a pavement structure design and maintenance strategy suitable for deterioration characteristics among regional construction and management administrations will be established.