This research addresses the critical challenge of accurately discriminating inrush currents within differential relays, a key component of power transformer protection systems. Differential relays distinguish genuine internal faults from transient events, such as inrush currents and external faults. Failure to make this distinction can lead to false tripping, which, in turn, may result in significant operational disruptions and economic losses. The study employs Discrete Wavelet Transform (DWT) and Adaptive Neuro-Fuzzy Inference System (ANFIS) techniques to develop reliable and intelligent protection systems. This intelligent system distinguishes internal faults from inrush currents and external faults. This system improves traditional remedies such as harmonic blocking and restrain and wave shape recognition techniques. The paper discusses the project’s methods, MATLAB/Simulink simulations, and implications for power transformers in electrical grid stations. The results indicated that this system accurately discriminated inrush currents with a 100% success rate and 91.5% accuracy at a speed of 3.5 ms.