A major challenge in quantitative biological Raman spectroscopy, particularly as applied to transcutaneous Raman spectroscopy measurements, is overcoming the deleterious effects of scattering and absorption (turbidity). The Raman spectral information is distorted by multiple scattering and absorption events in the surrounding medium, thereby diminishing the prediction capability of the calibration model. To account for these distortions, we present a novel analytical method, that we call turbidity-corrected Raman spectroscopy (TCRS), which is based on the photon migration approach and employs alternate acquisition of diffuse reflectance and Raman spectra. We demonstrate that, upon application of TCRS, the widely varying Raman spectra observed from a set of tissue phantoms having the same concentration of Raman scatterers but different turbidities has a tendency to collapse onto a single spectral profile. Furthermore, in a prospective study that employs physical tissue models with varying turbidities and randomized concentrations of Raman scatterers and interfering agents, a 20% reduction in prediction error is obtained by applying the turbidity correction procedure to the observed Raman spectra.