Random Forests as a Predictive Model in Clinical and School Psychology: Between Theory and Practice

Authors

  • Dr. Hocine Adli , Dr. Hanni Souleymane , Dr. Kaouthar BenNaceur , Dr. Talal Guenfoud

Keywords:

Random Forests; Predictive Models; Machine Learning; Clinical  Psychology; School Psychology; Learning Disabilities; Psychological Prediction; Decision Trees.

Abstract

This article aims to elucidate thegrowing role of machine learning-based predictive models in clinical and schoolpsychology, with a particular focus on theRandom Forest (RF) algorithm 

 

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References

Ahmed, S., Malik, A., & Tariq, R. (2022). Predicting students’ academic performance using machine learning: A case of secondary education. Education and Information Technologies, 27(1), 6585. https://doi.org/10.1007/s10639-02110704-2

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Published

2026-02-05

How to Cite

Dr. Hocine Adli , Dr. Hanni Souleymane , Dr. Kaouthar BenNaceur , Dr. Talal Guenfoud. (2026). Random Forests as a Predictive Model in Clinical and School Psychology: Between Theory and Practice. Pegem Journal of Education and Instruction, 16(1), 1870–1887. Retrieved from https://pegegog.net/index.php/pegegog/article/view/4894

Issue

Vol. 16 No. 1 (2026): PEGEGOG

Section

Article

License

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