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Protection mechanisms are essential to prevent catastrophic failures and ensure power network stability. However, accurately identifying and characterising power flows remains challenging, especially when fault resistance and location change. Incorrect fault identification may cause overall system instability and loss of synchronisation. This work presents a novel protection method to improve fault detection and reduce power swings by integrating a fuzzy inference system (FIS) with distance relays and a specialized proposed stability boundary curve. This method effectively differentiates between stable, critical, and unstable power swings, using fuzzy logic to enhance the sensitivity and accuracy of fault and power swing diagnosis. The proposed system allows intelligent load-shedding strategies to restore system stability when needed and can adapt to various fault resistances and locations. The protection system combines the distance relay, the stability boundary curve, and a Sugeno-type FIS. The technique was validated through MATLAB/Simulink simulations on a power system consisting of three buses and two generators. Simulations on a 700 km transmission line demonstrated the system’s efficiency in both fast fault detection (T2) and precise stability evaluation (T4-T2). Load-shedding strategies were applied, which contributed to system recovery, demonstrating the reliability and strength of the proposed system in avoiding major outages.