Abstract: Silkworm, Bombyx mori, is a very important economically exploited insect in South East Asia and revealing its genetic variation and diversity among genetic stock and appropriate classification method is needed for identification of potential parents. In the present study, the genetic divergence in 56 silkworm genotypes on 13 important qualitative and quantitative traits using Self Organizing Maps (SOM) was analyzed through cluster analysis. The highest level of genetic diversity were found in polyvoltine breeds by dividing into 8 different clusters and 6 clusters among bivoltine shown in two dimensional images called Kohonen maps. This clustering method allowed to divide the observations into several subclusters in such a way that homogeneity was obtained inside the sub-clusters and heterogeneity among the sub-clusters. Popular genotypes like Pure Mysore (PM), Nistari (NT-M, NT-P) were included in the cluster with 21.875% intra cluster difference among polyvoltine genotypes. Further, NB4D2-1 included in the cluster with 16.66% intra cluster differences along with other among bivoltine genotypes. It respectively indicates possibility of their exploitation in the field. There are numerous applications involving in the SOM algorithm but the most widespread employ was the identification and visualization of natural clustering in the data. Results indicated better ascertaining on the genetic diversity and genetic background on these silkworm genotypes provide ample scope to utilize them to achieve the desired objectives of highly heterotic silkworm hybrids to increase silk productivity in this region were discussed for the first time.