Student Performance Predictive Model Using Machine Learning

Develop a comprehensive predictive model using scikit-learn that forecasts student academic performance across multiple subjects. The model should incorporate historical grade data, attendance records, demographic information, and extracurricular engagement. Create a modular Python script that can handle different dataset structures, with built-in feature engineering for categorical variables and robust error handling. Include model interpretability metrics and generate a detailed performance report explaining key predictive factors.