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  3. Volume 12, Number 4, 2025
  4. Predicting Student Performance in Moroccan Secondary Education: A Machine Learning Framework for Academic Pathway Guidance

Predicting Student Performance in Moroccan Secondary Education: A Machine Learning Framework for Academic Pathway Guidance

MMC.
2025;
Volume 12, Number 4
: pp. 1135–1144
Received: March 28, 2025
Revised: October 19, 2025
Accepted: October 25, 2025

Sammah S., Ait Daoud M., Achtaich K., Tragha A.  Predicting Student Performance in Moroccan Secondary Education: A Machine Learning Framework for Academic Pathway Guidance.  Mathematical Modeling and Computing. Vol. 12, No. 4, pp. 1135–1144 (2025) 

Authors:
  1. S. Sammah
  2. M. Ait Daoud
  3. K. Achtaich
  4. A. Tragha
1
LTIM, Department of Computer Science, Faculty of Sciences Ben M'sick, Hassan II University of Casablanca
2
LTIM, Department of Computer Science, Faculty of Sciences Ben M'sick, Hassan II University of Casablanca; ORDIPU, Faculty of Sciences Ben M'sick, Hassan II University of Casablanca
3
LTIM, Department of Computer Science, Faculty of Sciences Ben M'sick, Hassan II University of Casablanca
4
LTIM, Department of Computer Science, Faculty of Sciences Ben M'sick, Hassan II University of Casablanca

This study addresses the lack of region-specific tools for academic counseling in Morocco by proposing a machine learning framework to predict student performance across secondary education pathways.  Using academic records of students from the Greater Casablanca region, we evaluate four models – Random Forest, Support Vector Machine (SVM), Decision Tree, and Linear Regression – following a methodology that integrates data preprocessing, feature selection, and synthetic data enrichment to address class imbalance.  The Random Forest algorithm achieved an accuracy rate of 75.20%, significantly outperforming the other models.  By linking predictive outcomes to actionable academic guidance, the proposed framework enables educators to recommend pathways tailored to individual student strengths, thus addressing a critical gap in Morocco's education system.

data mining
student performance
predictive modeling
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