Abstract
The purpose of this study was to predict an academic achievement model based on cardiorespiratory fitness (CRF) and body mass index (BMI) in ninth-graders. The study sample included 6 530 adolescents from 341 public schools in Slovakia. Criterion-referenced competency tests measuring academic performance in mathematics and mother language (Slovak), CRF, and BMI were assessed in the academic year 2022-2023. The results from the Random Forest Regression (RFR) machine learning algorithm suggest that adolescents who meet the international CRF and BMI criterion-referenced standards have a higher probability of getting a higher academic achievement score than unfit students with overweight or obesity. The chances of achieving the highest level of academic performance rose by 165% in mathematics and by 484% in mother language for boys who were fit and of normal weight compared to unfit boys with obesity. Unfit boys with obesity and unfit overweight girls had significantly lower odds of having the highest level of academic achievement compared to fit and normal-weight adolescents in mathematics (OR = 0.38; 95% CI, 0.20-0.71; p = 0.003; OR = 0.32; 95% CI, 0.18-0.55; p < 0.001) and mother language, respectively (OR = 0.17; 95% CI, 0.09-0.34; p < 0.001; OR = 0.17; 95% CI, 0.08-0.38; p < 0.001). Our results suggest that CRF is a significant predictor, with fit and normal-weight boys showing higher odds of better academic performance, but the model's modest predictive power suggests other factors also play a role.