Being molecularly heterogeneous, breast cancer tends to be a complicated oncological disease with high incidence rates throughout the world. The primary aim of this study was to identify the set of serum proteins with discriminatory capabilities towards the four major subtypes of breast cancer. We employed multipronged quantitative proteomic approaches like 2D-DIGE, iTRAQ and SWATH-MS and identified 307 differentially regulated proteins. Luminal A subtype consisted of 24, Luminal B subtype 38, HER2 Enriched subtype 17 and Triple negative breast cancer subtype 10 differentially regulated subtype specific proteins. These specific proteins were further subjected to bioinformatic analysis viz. PANTHER, DAVID and LENS which revealed the involvement in platelet degranulation, fibrinolysis, lipid metabolism, immune response, complement activation, blood coagulation, immune cell activation, glycolysis, amino acid biosynthesis and cancer signaling pathways in the subtypes of the breast cancer. The significant discrimination efficiency of the models generated through multivariate statistical analysis was decent to distinguish each of the four subtypes from controls. Further, some of the statistically significant differentially regulated proteins were verified and validated by immunoblotting and mass spectrometry based selected reaction monitoring (SRM) approach. Our Multipronged proteomics approaches revealed panel of serum proteins specifically altered for individual subtypes of breast cancer.