Abstract
A methodology for maintenance and rehabilitation strategies for high-volume roads based on developed pavement distress models is presented. Historical data of pavement distress on urban main roads in cities across Saudi Arabia were used to generate prediction models for common pavement distress. A sigmoid function was found to be the best fit for the data and seven prediction models for different types of pavement distress were developed. Based on these models, project-level maintenance and rehabilitation strategies for urban main roads are proposed.