Comprehensive Student Retention Predictive Analytics Model

Design an advanced Excel workbook that predicts student retention risk using machine learning-inspired predictive modeling techniques. Develop a multi-variable analysis framework that incorporates academic performance, attendance, socioeconomic factors, and historical dropout patterns. Create a dynamic risk scoring system with conditional formatting that automatically flags students at high risk of dropping out. Include scenario modeling capabilities that allow administrators to test intervention strategies and their potential impact on student retention.