Near infrared refl ectance (NIR) spectroscopy was used in combination with chemometrics to discriminate between fi shmeal, meat meal and soya meal samples. Samples were obtained from commercial feed mills and scanned in the NIR region (1100 - 2500 nm) in a monochromator instrument in refl ectance mode. Principal component analysis (PCA) and linear discriminant analysis were used to classify samples based on their NIR spectra. Full cross-validation was used in the development of classifi cation models. Partial least squares-discriminant analysis (PLS-DA) correctly classifi ed 85.7% of the fi shmeal samples and 100% of the meat meal and soya meal samples. These results demonstrate the usefulness of NIR spectra combined with chemometrics as an objective and rapid method to classify fi shmeal, meat meal and soya meal samples. NIR spectroscopic methods can be easily implemented in food mills and may be most useful for initial screening at early stages in the food production chain, enabling more costly methods to be used selectively for suspected specimens.