In garment production engineering, sizing system plays an important role for manufacturing of clothing. The standards for defining the size label are a critical issue. Locating the right garment size for a customer depends on the label as an interface. In this research work intend to approach that it could be used for developing sizing systems by data mining techniques applied to Indian anthropometric dataset. We propose a new approach of two-stage data mining procedure for labelling the shirt types exclusively for Indian men. In the first stage , clustering technique applied on the original dataset, to categorise the size labels. Then these clusters are used for supervised learning in the second stage for classification. A sizing system classifies a specific population into homogeneous subgroups based on some key body dimensions. The space with these dimensions gives raise to complexity for finding uniform standards. This enables us to have an interface as a communication tool among manufacturers, retailers and consumers. This sizing system is developed for the men’s age ranges between 25 and 66 years. Main attribute happens to be the chest size as clearly visible in the data set. We have obtained classifications for men’s shirt attributes based on clustering techniques.