Samples of magnesium stearate monohydrate and dihydrate were used to prepare standard mixtures of known pseudopolymorphic composition. Near infrared spectra (NIR) of the standard mixtures were measured to develop multivariate calibration models for the pseudopolymorphic composition of magnesium stearate by partial least squares (PLS) regression. Magnesium stearate hydrate compositions of the standard mixtures were compared against the hydrate composition based on thermogravimetric analysis (TGA). The mixture compositions determined from TGA mass loss on drying (LOD) measurements were found to be inaccurate. PLS regression was applied to the TGA thermograms of the standard mixtures to generate more accurate reference values, and this model was then applied to a set of validation samples. Application of the NIR PLS model to the validation sample set resulted in precise estimates of sample pseudopolymorphic composition when compared to the TGA PLS reference values. The NIR PLS model was found to be more sensitive than TGA LOD to small quantities of hydrates, and the TGA PLS model was also found to be more sensitive that TGA LOD. The results demonstrate the challenges and opportunities that arise when rapid, nondestructive spectroscopic methods depend on insensitive or inaccurate reference methods for development of multivariate calibration models.