This paper reviews the application of principal soft computing techniques for the study of textile processes and products. Soft computing suggests a new computing methodology that is both flexible and easy. Three major branches of soft computing, namely fuzzy logic, neural networks, and genetic algorithms, are discussed in detail with respect to their applications in solving variety of textile problems ranging from fibre classification, color grading, yarn and fabric property prediction, to the optimization of products and processes and even to search for a pleasing garment design. These tools of soft computing are complementary rather than competitive. Number of prediction models of 'hybrid type' are being developed combining the merits of each of these techniques. These hybrid models will help in establishing a prediction system that is more intelligent and effective in problem solving.