This paper presents a study about the possibility of system identification for a simulated moving bed (SMB), which is an important step for developing a smart SMB automatic control mechanism with a precise control capability. An SMB is a very complex and nonlinear system that is constructed from multiple columns in series and complex valve arrangements. All feed mixtures and solvents and the desorbent flow are controlled by the columns and valve devices at a fixed switching time. Thus, if the operational behavior of an SMB system can be identified in advance, then the precise control of the system can be achieved easily. In this study, the neural network (NN) technique was used to identify an SMB system. From the experimental results shown, an NN was found to be a very effective tool for SMB system identification.