The aim of this study was to evaluate the efficacy of a multi-analytical approach for origin authentication of cocoa bean shells (CBS). The overall chemical profiles of CBS from different origins were characterized using diffuse reflectance near-infrared spectroscopy (NIRS) and attenuated total reflectance mid-infrared spectroscopy (ATR-FT-IR) for molecular composition identification, as well as inductively coupled plasma-optical emission spectroscopy (ICP-OES) for elemental composition identification. Exploratory chemometric techniques based on Principal Component Analysis (PCA) were applied to each single technique for the identification of systematic patterns related to the geographical origin of samples. A combination of the three techniques proved to be the most promising approach to establish classification models. Partial Least Squares-Discriminant Analysis modelling of fused PCA scores of three independent models was used and compared with single technique models. Improved classification of CBS samples was obtained using the fused model. Satisfactory classification rates were obtained for Central African samples with an accuracy of 0.84.