This research affords an intensive analysis, which aims to improve the performance of a difference relay designed to protect 10 kVA transformers, especially using an artificial nervous network (Ann), TTUX10 models from Polylux. The origin of the study involves a comparative assessment between the traditional difference relay and an advanced intelligent relay system improved by the neural network. This analysis emphasizes the accuracy and addiction of the relay to identify a variety of symmetrical and weird errors that can affect the transformer’s performance. By using MATLAB for simulation, research explains how the neural network can effectively monitor and analyze the current on both the primary and secondary sides of the transformer. Ann is carefully designed to determine the most optimal travel parameters. When there is an error, the system immediately activates the “Trip” signal for the power switch (CB), which helps prevent damage and improve the safety and performance of the transformer. The expected results include a significant improvement in the speed and accuracy of the error, which contributes to the stronger and responsive protective system for electrical transformers. This study not only shows the viability of using Ann in transformer protection, but also emphasizes its widespread impact on the future of smart network development and energy security.