Cooperative work with Vistra continues to refine machine learning models that classify and interpret firewall rules for power grid operations. Sample firewall data was analyzed with Random Forest and AdaBoost algorithms, reaching accuracy rates between 88% and 99%. Additional refinements aim to expand model generalization, improve policy recommendations, and enhance proactive risk-based mitigation in operational environments.