This study proposes a simplified structural model called the Educational Decision Index (EDI) as a predictive analytics-based educational marketing tool for adaptive higher education program design. The model integrates five decision dimensions—motivation, modality, innovation, duration, and digital interest—into a weighted system capable of estimating the structural probability of enrollment. Unlike traditional descriptive approaches, the EDI enables marginal elasticity identification, predictive segmentation, and simulation of curricular redesign scenarios prior to implementation.

Methodologically, the model follows a quantitative explanatory–predictive design incorporating construct validation, variable normalization, and multivariate segmentation techniques. A multi-layer adaptive architecture—data capture, analytical engine, and strategic response—is proposed, transforming educational marketing into a continuous institutional intelligence system.

Expected results suggest improved predictive accuracy compared to conventional models and enhanced capacity to prioritize high-impact variables across decision clusters. Overall, the EDI framework integrates technology adoption theory, human capital economics, and advanced analytics into an operational governance model for adaptive educational strategy.