Effective scheduling and resource-leveling are the keys to successfully completing construction projects. Construction management must, therefore, find a way to overcome the challenges brought about by large fluctuations in resource usage. Metaheuristic methods have proved to be one of the most promising solutions for optimizations. This thesis aims to evaluate the application of Ant Colony Optimization (ACO) in the scheduling and resource-leveling of construction projects, research its adaptability, compare its performance with traditional methods such as (fundamental methods and heuristic methods), and identify its strengths and limitations. The methodology will be evaluating the scheduling and resource-leveling for an existing case study in Jordan, a firefighting building, and then comparing it with a rescheduled version using the ACO technique. The evaluation uses nine different objective functions that had been used by various researchers to obtain a leveled resource histogram. In addition, the Rate of Resource (RR) and Resource Improvement Coefficient (RIC) will be used as a basis for comparing the results of these indices. The used algorithm achieved the best optimization results by the index of the minimization of the sum of the sequence of the daily resource usage with an optimization percentage of 11%. This result demonstrates that the algorithm successfully optimized the scheduling and resource-leveling of the case study project. However, the extent of optimization may be contingent upon the underlying characteristics of a project so the outcomes may differ from one project to another. It is recommended to use all the relevant indices and only after evaluation choose the one that results in the best scheduling and resource-leveling.