Objective: This research aimed to use Machine Learning algorithms and the GPT natural language model to predict and improve students' performance. Originality: This study innovates in the educational field by employing advanced techniques of Machine Learning and GPT, enabling more personalized approaches that positively affect the quality of student learning. Method: The study adopted a quantitative, descriptive, and explanatory approach, based on applied research and experimental methods, processing 900 records using 21 algorithms. Results: The effectiveness of the algorithms in predicting students' performance stood out. The use of GPT proved particularly beneficial in enhancing student performance, surpassing other training approaches. These techniques find knowledge gaps and provide personalized feedback, allowing for individualized education. Conclusion: The combination of GPT with machine learning is a valuable tool for enhancing the quality of education and the learning experience, fostering significant advancements in the educational field.