A novel, pattern-recognition-based approach for fast detection of power islands in a distribution network is investigated. The proposed method utilizes transient signals generated during an islanding event to detect the formation of the island. A decision-tree classifier is trained to categorize the transient generating events as “islanding” or “non-islanding.” The feature vectors required for classification were extracted from the transient current and voltage signals through discrete wavelet transform. The proposed technique is tested on a medium-voltage distribution system with multiple distributed generators. The results indicate that this technique can accurately detect islanding events very fast.