Bread wheat (Triticum aestivum L.) germplasm lines were subjected to multivariate analysis for five agromorphological traits using augmented experimental design. The germplasm lines formed four clusters based on the estimates of genetic diversity using Un-weighted Pair Group Method with Arithmetic mean (UPGMA) algorithm. On the basis of their greater intercluster distance, high value of cluster mean according to the character to be improved and performance of the individual germplasm for the character, the germplasm could be used in hybridization programme for improvement of different plant characters. From principal component analysis (PCA) the first three principal components explained 83.60% of the total variation, suggesting that traits such as plant height, days to flowering and maturity and grain yield are the principal discriminatory traits in the germplasm. The diverse parents from various clusters are helpful in planning and broadening the breeding programme by planning the crosses and increased use of heterosis and genetic diversity especially for grain yield in our country. It is concluded that the genetic variation existing in the germplasm set can efficiently be utilized in genetic improvement of bread wheat.