In the current educational context, physical education and student sports development face challenges marked by continuous technological evolution. This study proposes a predictive model supported by machine learning and artificial intelligence (AI), establishing a connection between cardiorespiratory capacity (VO2max) and student anthropometric data. With a sample of 179 students aged 13 to 18, the model-building process included preparing and partitioning a dataset, training, and evaluation under the CRISP-DM methodology. A multiple linear regression model was applied, incorporating weight, age, height, sex, and body mass index (BMI) to analyze their relationship with the dependent variable (VO2max). Performance metrics revealed a significant correlation between anthropometric measurements and cardiorespiratory fitness (CRF), with a 24% improvement in training, although test accuracy w...