The study examines the potential of artificial intelligence (AI) in education, focusing on predicting student performance and optimizing learning outcomes. A literature review of 25 studies (2018–2024) identified key trends, challenges, and ethical concerns, including curriculum integration and accessibility of AI tools for underprivileged learners. Using the Student Performance Dataset, which includes demographic, academic, and behavioral features of Portuguese secondary school students, machine learning models such as logistic regression, KNN, SVM, random forest, and decision trees were employed to predict final grades (G3). Model accuracy was improved through hyperparameter tuning and an ensemble approach using a Voting Classifier, with cross-validation ensuring stability. The findings emphasize the potential of AI to revolutionize education by enabling personalized learning, enhancing prediction accuracy, and addressing individual needs. Nonetheless, privacy and ethical challenges persist. Future research should focus on AI curriculum integration and sustainable applications to fully realize its benefits in education.