In this study, a decision support system has been developed for land mine detection and classification. Data obtained from detector based magnetic anomaly have been used to classify the land mines. With this classification, it is decided that whether obtained data belongs to a land mine or not, and the type of mine. The meta-heuristic k-NN classifier (HKC) has been used in developed decision support system. Consequently, it is seen that decision support system detects the presence of mines and decides the type of mine with 100% success for measurements in a certain range, and the proposed classifying method shows much higher performance than traditional instance-based classification method.