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Domestic cow, Bos taurus is one of the important species selected by humans for various traits, viz. milk yield, meat quality, draft ability, resistance to disease and pests and social and religious reasons. Since cattle domestication from Neolithic (8,000-10,000 years ago) today the population has reached 1.5 billion and further it’s likely to be 2.6 billion by 2050. High magnitude of numbers, breed management, market need of traceability of breed product, conservation prioritization and IPR issues due to germplasm flow/exchange, has created a critical need for accurate and rapid breed identification. Since ages the defined breed descriptors has been used in identification of breed but due to lack of phenotypic description especially in ova, semen, embryos and breed products molecular approach is indispensable. Further the degree of admixture and non-descript animals characterization, needs of molecular approach is imperative. Till date breed identification methods based on molecular data analysis has great limitations like lack of reference data availability and need of computational expertise. To overcome these challenges we developed a web server for maintaining reference data and facility for breed identification. The reference data used for developing prediction model were obtained from8 cattle breeds and 18 microsatellite DNA markers yielding 18000 allele data. In this study various algorithms were used for reducing number of loci or for identification of important loci. Minimization up to 5 loci was achieved using memory-based learning algorithm without compromising with accuracy of 95%. This model approach and methodology can play immense role in all domestic animal species across globe in breed identification and conservation programme. This can also be modelled even for all flora and fauna to identify their respective variety or breed needed in germplasm management.