Road construction projects in Iraq require a developmental study of the planning process toward building computerized management systems. In this thesis, a management system has been built, based on artificial neural networks and genetic algorithms. The proposed software estimates the optimal number of equipment, machineries, and relevance instruments required according to progress table of the work during the proposed implementation period of the project. Artificial neural network systems have been adopted to build models to predict the productivity of the equipment used in road construction projects, based on the factors that affecting the productivity of these mechanisms. By implementing the system and simulating at road project, several conclusions have been conducted. One of the most important conclusions is that the optimal distribution of the numbers and types of machineries used in road construction has a significant impact on the time of implementation of project.