Public safety agencies are increasingly caught between unpredictable emergency call volumes and the limitations of traditional, manual scheduling. This white paper explores how the integration of machine learning and predictive modeling can transform workforce management from a reactive process into a proactive, data-driven strategy. By analyzing variables such as weather patterns, local events, and seasonal trends, these AI-enhanced frameworks allow agencies to forecast public safety call volume with unprecedented accuracy. The result is a more resilient operational model that reduces employee burnout, cuts unnecessary overtime costs, and ensures that critical resources are exactly where they need to be when every second counts.