In order to overcome the limitation of the accuracy and efficiency of a single classifier, Remote Sensing Multiple Classifier System (RSMCS) is proposed. The system is able to combine the advantages of diffident classifiers and in the meantime acquires higher accuracy than that for a single classifier. According to the characteristics of remote sensing images and the acquirement of classifications, based on the requirement analysis and design for the system, the system is developed by using IDL language on the ENVI remote sensing information processing platform. The major functions of the system include remote sensing image file processing module, image feature selection and extraction module, remote sensing image classification pre-processing module, and remote sensing multiple classifier ensemble module (fixation combination style, user-defined style, wizard style, and recommend style). Furthermore, two experiments are presented to illustrate that the system could effectively improve the accuracy of remote sensing image classification.