Rezqallah Hasan Fayyadh. Ramadhan2022-05-182022-05-184835https://drepo.sdl.edu.sa/handle/20.500.14154/2268Pavement represent an important asset to all nations. In Saudi Arabia huge investments have been made in constructing enormous pavement networks of roads and airfields. These networks require great care and attention through conducting continuous evaluation and timely maintenance to keep them operating under acceptable levels of service. Pavement condition prediction models can greatly enhance the capabilities of a pavement mangement system (PMS). Among other benefits, these models allow pavement authorities to predict the timing of maintenance or rehabilitation activities and to estimate the long-range funding requirements for preserving the payment system. In this study, pavement condition-related data were collected from all accessible sources in the Kingdom, including the Ministry of Communications, the Municipality of Riyadh, the Municipality of Dammam, the Industrial City of Al-Jubail, and from other research studies carried out by different researchers. These data were categorized, processed, analyzed and used to generate different prediction models from the related factors affecting the pavement condition. These models were evaluated to identify the most appropriate ones fitting the available data. The obtained models could adequately predict the pavement condition from the validation data with a reasonable level of significance. On the other hand, opinions of different groups of individuals from all around the Kingdom about the weights of the factors affecting the maintenance priority ranking were collected. The collected data were checked for reliability and repeatability and then usd to obtain a general priority index procedure. This proceduer is used for ranking pavement sections in any network according to their importance or urgency for maintenance. The procedure was validated using two case studies, where it was concluded that the procedure could adequately duplicate the engineering judgment for maintenance priority ranking in addition to its capability to handle huge pavement networks systematically and efficiently. The developed models and procedures were integrated into one sub-system that can handle data entry, retrieval and results reporting. This sub-system can be integrated in any pavement management system to complement other activities and to obtain a comprehensive PMS.enThesis