In this work, Raman spectroscopy was successfully used for the quantitative determination of the liquid phase concentration in an aqueous polymorphic system of D‐mannitol. An extensive study has initially been performed to identify the influence of the solid state, e.g. particle size, particle amount, and different polymorphs, on the intensity of the characteristic Raman solute signal. It was found that the existence of solid phase can decrease Raman intensity, and this influence is more significant when the suspension density is higher, e.g. with smaller size and larger amount of particles. Based on this information, a large number of samples were examined by Raman spectroscopy in the form of clear solutions and suspensions. The spectral preprocessing and partial least squares (PLS) regression were then used to relate the solute concentrations to these spectral data, independent of solid state. Several PLS calibration models were developed with different treatments to the spectral data, and the optimized strategy was finally demonstrated. Particularly, a reference peak at 578 cm−1 related to the sapphire in the Raman probe window was innovatively applied to reduce the influences from the equipment and other external variations, with which the full‐spectrum PLS model was seen to give more stable results rather than partial spectral regions. The optimized model was subsequently applied to predict the liquid phase concentration in a multiphase multicomponent dynamic process, the solvent mediated polymorphic transformation (SMPT) of mannitol, and it was shown that the offline measurements and the predicted values were mainly in agreement with one another. Copyright © 2015 John Wiley & Sons, Ltd.