The aim of this work was to assess the effect of different crystalline polymorphism on surface energetics of D-mannitol using finite dilution inverse gas chromatography (FD-IGC). Pure α, β and δ polymorphs were prepared via solution crystallisation and characterised by powder X-ray diffraction (P-XRD). The dispersive surface energies were found to range from 43 to 34 mJ/m(2), 50 to 41 mJ/m(2), and 48 to 38 mJ/m(2) , for α, β, and δ, respectively, for surface coverage ranging from 0.006 to 0.095. A deconvolution modelling approach was employed to establish their energy sites. The primary sites corresponded to maxima in the dispersive surface energy of 37.1 and 33.5; 43.3 and 39.5; and 38.6, 38.4 and 33.0; for α, β, and δ, respectively. This methodology was also extended to an α-β polymorph mixture to estimate the amount of the constituent α and β components present in the sample. The dispersive surface energies of the α-β mixture were found to be in the range of 48 to 37 mJ/m(2) with 40.0, 42.4, 38.4 and 33.1 mJ/m(2) sites. The deconvolution modelling method extracted the energy contribution of each of the polymorphs from data for the polymorphic mixture. The mixture was found to have a β-polymorph surface content of ∼19%. This work shows the influence of polymorphism on surface energetics and demonstrates that FD-IGC coupled with a simple modelling approach to be a powerful tool for assessing the specific nature of this energetic distribution including the quantification of polymorphic content on the surface.