Student Performance Prediction System

Academic performance evaluation plays a crucial role in shaping students’ future learning outcomes. Traditional assessment methods often rely on periodic examinations, which may fail to identify learning difficulties early on. This delay can result in academic failure, reduced confidence, and ineffective teaching methods. This paper presents a Student Performance Prediction System designed to analyze student data and predict academic performance at an early stage. The proposed system consists of multiple interactive modules, including user authentication, student personal information management, educational data collection, subject-wise question and answer analysis, and performance prediction visualization. By applying data-driven analysis techniques, the system predicts student performance in both graphical and descriptive formats. It highlights weak areas where students require additional support and helps teachers identify learners who need additional guidance. The main objective of this system is to support students and teachers through early prediction, reduce academic failure, save evaluation time, and improve overall learning outcomes of students. The proposed model is highly useful for schools and colleges because it makes the evaluation process smarter, faster, and more accurate..