Raman spectroscopy (RS) has been extensively explored as an alternative diagnostic tool for breast cancer. This can be attributed to its sensitivity to malignancy-associated biochemical changes. However, biochemical changes due to nonmalignant conditions like benign lesions, inflammatory diseases, aging, menstrual cycle, pregnancy, and lactation may act as confounding factors in diagnosis of breast cancer. Therefore, in this study, the efficacy of RS to classify pregnancy and lactation-associated changes as well as its effect on breast tumor diagnosis was evaluated. Since such studies are difficult in human subjects, a mouse model was used. Spectra were recorded transcutaneously from the breast region of six Swiss bare mice postmating, during pregnancy, and during lactation. Data were analyzed using multivariate statistical tool Principal Component–Linear Discriminant Analysis. Results suggest that RS can differentiate breasts of pregnant/lactating mice from those of normal mice, the classification efficiencies being 100%, 60%, and 88% for normal, pregnant, and lactating mice, respectively. Frank breast tumors could be classified with 97.5% efficiency, suggesting that these physiological changes do not affect the ability of RS to detect breast tumors.