New analytical tools that enable analytical laboratories to quantitatively and qualitatively analyze alternative and renewable solid biofuels are needed. Fourier transform infrared (FTIR) spectroscopy was applied in combination with a two-step multivariate modelling procedure. In the first instance, a C&RT (classification and regression trees) model was developed and validated for use in distinguishing different biomass origins and possible sources of contamination. Once the solid fuels were correctly identified, the model was used to predict the concentrations of individual components using partial least squares regression (PLSR) models. The first C&RT model differentiated between the different classes of biofuel origins. Using the absorption intensity in the wave-number range of 1800-400 cm(-1), the prediction had a recovery of between 92% and 99%. The second C&RT model differentiated between the possible sources of contamination, which could be predicted with a recovery between 76% and 91% based on the FTIR results. Accuracy profiles based on the analysis results of validation samples were then calculated to prove the reliability of the developed regression models. The developed spectroscopic methods rapidly and adequately determined (qualitative analysis) the origin of the biofuels and indicated the possible source of contamination. The effects of two spectral data pre-processing methods (PQN & SNV) were also compared based on the accuracy of the developed models.