Abstract: In the 2D non-contacted body measurement,the size of body girths can only be acquired indirectly by data transform from 2D to 3D.In order to increase the precision of the prediction of girth size,it is necessary to develop different prediction models in accordance with body types.To avoid the information overlapping,the principal component analysis is undertaken to sum up the initial 24 independent variables and reduce them to 4 independent variables for objective and comprehensive evaluation of body types.The function of fuzzy clustering analysis is used to make classification of body types whose prediction models are established respectively.The samples are classified on the principle of the maximum membership and the classification cluster validity are verified by F-statistic and the value of clustering validity function.And the optimal number of classification is determined through practical application.