The aviation industry is witnessing rapid advancements in the application of artificial intelligence (AI) technologies to improve engine efficiency and enhance aviation safety. The ability to predict potential failures before they occur is considered one of the most significant modern applications of these technologies, as it contributes to reducing unexpected malfunctions and improving the reliability of aircraft systems. Artificial intelligence systems rely on analyzing data collected by sensors installed in aircraft engines, including temperature, pressure, vibration, and rotational speed, to detect abnormal changes that may indicate the early stages of technical malfunctions. Through machine learning algorithms, these systems can estimate the likelihood of component deterioration and determine the appropriate time to perform maintenance before problems become more severe. These technologies contribute to the development of predictive maintenance, an approach that relies on the actual condition of the engine rather than depending solely on scheduled maintenance or waiting for failures to occur. This approach helps reduce aircraft downtime, improve maintenance efficiency, optimize the use of technical resources, and support the decision-making processes of specialized engineers. Despite the importance of artificial intelligence in this field, achieving reliable results requires accurate data, specialized engineering testing, continuous human supervision, and compliance with established aviation safety standards. These technologies serve as supporting tools for engineers rather than replacements for technical expertise and officially approved maintenance procedures. In conclusion, the application of artificial intelligence in predicting aircraft engine failures represents a significant step toward a more advanced future in aviation engineering. It facilitates the transition from addressing failures after they occur to identifying early warning signs, thereby enhancing engine reliability and supporting the safety of flight operations.