The surface temperature of pavements is a critical attribute during pavement design. Surface temperature must be measured at locations of interest based on time-consuming field tests. The key idea of this study is to develop a temperature profile model to predict the surface temperature of flexible and rigid pavements based on weather parameters. Determination of surface temperature with traditional techniques and sensors are replaced by a newly developed method. The method includes the development of a regression model to predict the average annual surface temperature based on weather parameters such as ambient air temperature, relative humidity, wind speed, and precipitation. Detailed information about temperature and other parameters are extracted from the Federal Highway Administration's (FHWA) Long Term Pavement Performance (LTPP) online database. The study was conducted on 61 pavement sections in the state of Alabama for a 10-year period. The developed model would predict the average annual surface temperature based on the known weather parameters. The predicted surface temperature model for asphalt pavements was very reliable and can be utilized while designing a pavement. The study was also conducted on seven rigid pavement sections in Alabama to predict their surface temperature, in which a successful model was developed. The outcome of this study would help the transportation agencies by saving time and effort invested in expensive field tests to measure the surface temperature of pavements.