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Raman spectroscopy offers the potential for the identification of illegal narcotics in seconds by inelastic scattering of light from molecular vibrations. In this study cocaine, heroin, and MDMA were analyzed using near-IR (785 nm excitation) micro-Raman spectroscopy. Narcotics were dispersed in solid dilutants of different concentrations by weight. The dilutants investigated were foodstuffs (flour, baby milk formula), sugars (glucose, lactose, maltose, mannitol), and inorganic materials (Talc powder, NaHCO3,MgSO4 .7H2O). In most cases it was possible to detect the presence of drugs at levels down to ~10% by weight. The detection sensitivity of the Raman technique was found to be dependent on a numberof factors such as the scattering cross-sections of drug and dilutant, fluorescence of matrix or drug, complexity of dilutant Raman spectrum, and spectrometer resolution. Raman spectra from a series of 20 mixtures of cocaine and glucose (0 100% by weight cocaine) were collected and analyzed using multivariate analysis methods. An accurate prediction model was generated using a Partial Least Squares (PLS) algorithm that can predict the concentration of cocaine in solid glucose from a single Raman spectrum with a root mean standard error of prediction of 2.3%. Science & Technology Against Drugs Programme (Forbairt) peer-reviewed