Higher education faces mounting enrollment challenges—balancing class composition, revenue, and student fit amid complex decision cycles. Traditional methods relying on intuition and historical trends no longer suffice. This presentation introduces Othot’s AI-powered platform for enrollment management, which uses machine learning, predictive analytics, and explainable AI to move institutions from reactive to proactive strategies. Beyond forecasting enrollment likelihood, the platform enables prescriptive analytics—modeling “what-if” scenarios that reveal how financial aid, timing, and policy changes influence outcomes. Through its Phase Change simulation, Othot empowers leaders to shape undergraduate and graduate classes, optimize yield, maximize revenue, and align enrollment with institutional goals—transforming admissions into a precision-driven science.