The use of a combined spectral intensity and polarization signals optically scattered by tissue to determine analyte concentration in optically clear and turbid biological media was explored in a simulation study. Blood plasma was chosen as the biological model and glucose as the analyte of interest. The absorption spectrum and optical rotatory dispersion were modeled using experimental data and the Drude's equation, respectively, between 500 and 2000 nm. A polarization-sensitive Monte Carlo light-propagation model was used to simulate scattering media. Unfold partial least squares and multiblock partial least squares were used as regression methods to combine the spectral intensity and polarization signals, and to predict glucose concentrations in both clear and scattering models. The results show that the combined approaches produce better predictive results in both clear and scattering media than conventional partial least squares analysis, which uses intensity or polarization spectra independently. This improvement was somewhat diminished with the addition of scattering to the model, since the polarization signals were reduced due to multiple scattering. These findings demonstrate promise for the combined approach in clear or moderately scattering biological media; however, the method's applicability to highly scattering tissues is yet to be determined. The methodology also requires experimental validation.