Student Performance Prediction and Future Guidance System

This paper presents a system for predicting student performance and providing future academic guidance using data analysis and rule-based techniques. The system analyzes student data such as attendance, marks, and study patterns to predict academic outcomes. Based on the predictions, it suggests personalized guidance to help students improve their performance. The proposed model assists educators in identifying weak students early and enables timely intervention. Experimental results show that the system can effectively predict student performance with good accuracy.