Breast cancer is the most frequently occurring disease among women worldwide. The early stage of breast cancer identification is the key challenge in cancer control and prevention procedures. Although gene expression profiling helps to understand the molecular mechanism of diseases or disorder in the living system, gene expression pattern alone is not sufficient to predict the exact mechanisms. Current proteomics tools hold great application for analysis of cancerous conditions. Hence, the generation of differential protein expression profiles has been optimized for breast cancer and normal tissue samples in our organization. Normal and tumor tissues were collected from 20 people from a local hospital. Proteins from the diseased and normal tissues have been investigated by 2D gel electrophoresis and MALDI-TOF-MS. The peptide mass fingerprint data were fed into various public domains like Mascot, MS-Fit, and Pept-ident against Swiss-Prot protein database and the proteins of interest were identified. Some of the differentially expressed proteins identified were human annexin, glutathione S-transferase, vimentin, enolase-1, dihydrolipoamide dehydrogenase, glutamate dehydrogenase, Cyclin A1, hormone sensitive lipase, beta catenin, and so forth. Many types of proteins were identified as fundamental steps for developing molecular markers for diagnosis of human breast cancer as well as making a new proteomic database for future research.