A mathematical method, weighted euclidean distance, has been applied for indirect determination of total hand value from the KES-system parameters obtained for various summer knitted T-shirts. In this method the weight of multivariable concerned with fabric hand is  determined from objective measurements without any resource to subjective evaluation. Artificial neural network with back propagation learning algorithm and multiple linear regression algorithm have been used to construct a predictive models for determination of total hand value of summer knitted T-shirts based on fabric mechanical properties measured on the KES-system of each sample as input and total hand value predicted by mathematical model as desired output. The predcitve power of optimized models are caclulated and compared. The results reveal that the artifical neural network model is very effective for predicting the total hand value and   has the better performance as compared to multiple linear regression model