Artificial Intelligence Driven Predictive Analytics for Smart Education Systems

The rapid growth of Artificial Intelligence (AI) and Machine Learning (ML) technologies has significantlytransformed modern education systems. Smart education platforms are increasingly adopting predictiveanalytics to improve student performance, personalize learning experiences, and optimize institutionalmanagement. This research paper examines the role of AI-driven predictive analytics in smart educationsystems and analyzes its impact on academic performance, student engagement, and decision-makingprocesses. The study employs secondary data analysis and comparative evaluation of machine learningalgorithms including Decision Tree, Random Forest, Support Vector Machine (SVM), and Neural Networks.The findings indicate that AI-based predictive systems improve educational efficiency, reduce dropoutrates, and enhance personalized learning outcomes. The paper further discusses challenges related to dataprivacy, ethical concerns, and implementation barriers in educational institutions. The study concludesthat AI-powered predictive analytics has substantial potential to revolutionize education management andacademic delivery in the future.