The Near Infrared (NIR) spectroscopy is a novel technique that can be used for early identification and separation of minerals from unwanted gangue during ore sorting. In this research, the potential of near infrared sensors for application in automated sorting was investigated on a copper-gold ore sample. The ore contains a substantial amount of carbonaceous material which results in excessive acid consumption in the subsequent leaching process during copper extraction. To classify this unwanted gangue material (carbonate) from the valuable metal (copper), a strategy to identify and distinguish the ore according to copper and carbonate content was developed. The near infrared spectra were measured on the surface of ore particles and characteristic absorption features were observed at a longer wavelength ranging from 2000 nm to 2405 nm. The results were then correlated with the chemical and mineralogical composition of the ore determined using X-Ray fluorescence and X-Ray diffraction equipments respectively. The near infrared spectra showed distinct characteristic absorption features for carbonate rich particles that distinguished these from copper bearing particles, which are fairly featureless at longer wavelengths. Combined interpretation of spectral features and chemical and mineralogical data indicates that near infrared-based sorting has potential for this type of ore.