Abstarct: As the exploration task is usually encountered with risky situation and is also capital intensive, so optimum selection of prosperous regions will be a crucial process in mineral prospecting. One sophisticated method to acquire the goal is to use the remote sensing data and process them especially considering the pattern recognition techniques in order to receive some accurate results. Support vector machine (SVM) is a novel machine learning technology to be considered as a robust method in classification and regression tasks. This particular method was introduced in the early of 1990s and there are at least three reasons for its success namely, 1) ability to learn well with only a very small number of parameters and data, 2) its robustness against the noise, and 3) its computational efficiency compared with several other intelligent methods such neural network, fuzzy network and etc. Since, there is no evidence of using SVM in recognition of the promising exploration areas, this study has been performed with the main aim of utilizing SVM in recognition of the mineral potential areas in southwest of Masuleh, Gilan province, Iran. Pattern recognition in the mineral exploration works is relied on the modeling of the known mineral occurrences and be able to provide a chance to recognize the potential areas in terms of extracted features of training points. Therefore, in the present study, after the primary analyzing of available information and image processing of interested area, several suspected areas were indicated for field observation and geochemical exploration works. In the next stage, considering the geochemical anomalies as training set, the remote sensing data of the interested region together with all the other available data were then been processed and classified comprehensively using by supervised SVM algorithm. At the end by integrating all the obtained results including the ones of supervised SVM algorithm, 5 promising exploration areas were introduced as priority in a exploratory map and a few recommendation for further investigation has also been provided.