In this paper, 36 coats, which had different ease and made from different fabrics, were made and their profile appearance were evaluated by seven experts. These coats were scanned by using [TC]2 three dimensional body scanner and their three dimensional virtual pictures was shown according to the OpenGL software surface display theory. Key factors witch affected garments appearance ease most were selected as independent variables and trained in BP neural network to forecast garments profile appearance value. Fuzzy selecting rules were used to select the closest value from the 36 coats samples for the purpose of obtaining the pictures of corresponding three dimensional virtual garment profiles. So, viewable garment profile forecasting system, in which garment size and materials’ mechanical properties were known, was established and its veracity had been tested through experiment.