Nowadays, Multiple Criteria Decision Making(MCDM) is considered as one of the widely used branches of decision science. Due to attractiveness of the different facets of MCDM field which has lead many decision makers and researchers to utilize them, a lot of MCDM methods are developed. Great extensions in MCDM methods has baffled analysts and decision makers. They do not know which method is more appropriate for their desired problem. This makes decision makers hesitate to use MCDM methods. Therefore, designing approaches in order to suggest the most appropriate MCDM method to decision makers, according to the conditions of decision problem, is very important. Hence, in this thesis, an expert system to suggest the most suitable method to the decision makers is proposed. The system design process consists of four stages: 1- Determination of system requirements, 2- Function structure design of expert system, 3- Knowledge acquisition, and 4- Design of inference system. Hence, at first the basic requirements of an expert system are identified and then based on these requirements, function structure of the expert system is designed. For knowledge acquisition, 11 widely used methods in Multi-Attribute Decision Making(MADM) field have been selected and the required knowledge of these methods, based on criteria specified in the system requirements, have been collected and documented from the literature. This causes available knowledge in the system to be defensible and referable. After the knowledge acquisition from the literature, knowledge inference system is designed so that the expert system asks the user some questions about the characteristics of the decision problem and then suggests the most appropriate MCDM method regard to the responses. The main difference between the proposed expert system in this study with similar previous expert systems, is the integrity of its development process. Also the knowledge contained in this system has been collected from the literature in a documentary manner and is not limited only to implicit knowledge of an expert. Keywords: Selection of the most appropriate MCDM method, Comparison of MCDM methods, Multiple Criteria Decision Making(MCDM), Multi-Attribute Decision Making(MADM), Expert System.