This paper presents a new differential protection scheme based on support vector machine (SVM), which provides effective discrimination between internal faults in a power transformer with the other disturbances, such as various types of inrush currents and overexcitation conditions. The feature extraction is carried out using wavelet transform, which later, is given as input to the SVM classifier. Numerous simulation cases consisting of internal faults and other disturbances have been simulated with varying fault and system parameters for an existing power transformer of Gujarat Energy Transmission Corporation Ltd. (GETCO), Gujarat, India, using the PSCAD/EMTDC software package. The performance of the developed algorithm has been tested over a simulation data set of 5442 cases and the overall fault discrimination accuracy of more than 99% is achieved. It has also been observed that the SVM classifier gives highly promising results for CT saturation, different connection type, and various ratings of the transformer, even though it is trained only once for a single rating and connection of a transformer. At the end, a comparative evaluation of the proposed scheme is also carried out with other existing/proposed methods where it has been observed that the proposed method provides superior results.