Forward modeling is to model structural performance and optimize the relationship among material composition, process, and performance, and predict performance according to material composition and process prediction. Reverse optimization, an important research topic in material science and engineering, is to design composition and processes according to pre-performance design. Computational intelligence technique, a new point and interdisciplinary research focus, provides a new way to predict material properties. In this paper, we review and summarize methods of material design based on computational intelligence technique. As we know, establishing models of material data can optimize material composition and production processes, reduce testing cases and cost, and improve performance. This article also points out advantages, disadvantages and the future direction in the field of material design based on computational intelligence technique.