Abstract: A computer-implemented method for optimizing resource allocation using machine learning algorithms. The method receives input data from various sources, including project requirements, timelines, and project allocation, and analyze using machine-learning algorithms to prediction which entities are most suitable for given projects. The method generates a prioritized list of qualified entities and offers strategic recommendations for resource distribution. The machine-learning algorithm manages ongoing transactions, monitors compliance, and predicts future resource needs, comparing these predictions against project allocation thresholds. If predicted needs exceed the project allocation, the system issues warnings. An interface allows users to adjust resource strategies and monitor project progress through visual analytics dashboards.