The objective of this in vitro study was to explore the applicability of Raman spectroscopy to distinguish basal cell carcinoma from its surrounding noncancerous tissue; therefore, identifying possibilities for the development of an in vivo diagnostic technique for tumor border demarcation. Raman spectra were obtained in a two-dimensional grid from unstained frozen sections of 15 basal cell carcinoma specimens. Pseudo-color Raman images were generated by multivariate statistical analysis and clustering analysis of spectra and compared with histopathology. In this way a direct link between histologically identifiable skin layers and structures and their Raman spectra was made. A tissue classification model was developed, which discriminates between basal cell carcinoma and surrounding nontumorous tissue, based on Raman spectra. The logistic regression model, shows a 100% sensitivity and 93% selectivity for basal cell carcinoma. The Raman spectra were, furthermore, used to obtain information about the differences in molecular composition between different skin layers and structures. An interesting finding was that in four samples of nodular basal cell carcinoma, the collagen signal contribution in spectra of dermis close to a basal cell carcinoma, was markedly reduced. The study demonstrates the sensitivity of Raman spectroscopy to biochemical changes in tissue accompanying malignancy, resulting in a high accuracy when discriminating between basal cell carcinoma and noncancerous tissue.