System identification is a process of creating a mathematical model of a system from its external observations (inputs and outputs). The concept of discovering models from data is trivial in science and engineering fields. The goal of this chapter is to review the recent development in the field of System Identification from the Automatic Control perspective. In the first part of this chapter, we present a classification of design features of Industrial Control Systems (ICSs). Then we review the literature on system identification techniques for creating models of ICSs. The classification of ICSs allows us to identify limitations and unexplored challenges in the literature on system identification techniques.