Maintaining a well-functioning road infrastructure network is crucial for economic growth and social development. However, road authorities face the challenge of allocating limited funds to repair and maintain vast networks of roads. To support optimized repair decisions, this research proposes developing a decision support system (DSS) that integrates Agent based simulation modeling. The DSS will enable road authorities to evaluate the effects and benefits of different repair policies for road segments based on their importance and condition. The core of the DSS will be a simulation model created in Anylogic that represents the road network under different repair scenarios. The model is composed of two main modules: Repair procedure simulation and its Traffic Impact on the road network. Key road segments are differentiated based on functional class, traffic volumes, connectivity to socioeconomic centers, and other measures of importance. The DSS interface allows users to set repair rules and priorities. It incorporates multi-criteria decision analysis to weigh costs and benefits across segments. This supports optimal allocation of road maintenance funds, ultimately improving network conditions. With sound infrastructure repair policies, transportation agencies will reduce costs, enhance safety and mobility, and better serve diverse stakeholders. This research provides a valuable tool for road authorities seeking to sustain long-term quality of vital transportation assets.