Purpose: While artificial intelligence has been extensively used in many fields; some research has been done on its applications in the apparel industry. The aim of this study to predict the relationships among the body dimensions using artificial neural network technique.

Design/methodology/approach: Two hundred data had been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from the Uttar Pradesh, India by random sampling method. Artificial neural network technique was implemented to find out the relationships among the sizes of different body parts to be required for making ready-made garments.

Findings: In this study, drop value (the difference between the chest girth and the hip girth) had been taken as dependent variable and the age, height, weight, hip girth, abdomen girth are the input parameters under artificial neural network technique. Result shows most important variable is hip girth (100%) which affects the drop value and the second most important variable is round bust (95.8%). The percentage of importance of waist girth, round abdomen and age are 29.3%, 24.1% and 13.1% respectively.

Conclusions: Neural network is a type of artificial intelligence technique can predict the relationships among different body dimensions in a better way. Neural network has the capability to train itself on a sample population for finding the relationships among body dimensions and then can predict for the whole population which are to be importantly needed for making readymade garments.