This study examines the feasibility of using front-face fluorescence (FFFS), near-infrared (NIR), and mid-infrared (MIR) spectroscopies for the authentication of 100 extra virgin argan oil (EVAO) samples originated from 5 regions in Morocco (Chtouka, Essaouira, Sidi Ifni, Taroudant, and Tiznit) characterised by their different altitudinal levels, rainfall, and temperatures. Another objective of this study is to detect the adulteration of pure EVAO provided from the five regions with cheaper vegetable oils (peanut, walnuts, hazelnut, sunflower, grape, rapeseed, sesame, olive, and a mixture of the previous vegetable oils) at different levels (1, 5, 10, 20, 30, 40, and 50%) and predict the percentage of fraud. By applying principal component analysis and factorial discriminant analysis, to the emission spectra acquired after excitation wavelengths set at 430, 290, and 270 nm, a perfect discrimination between EVAO samples according to their geographical origin was observed achieving 100% of correct classification; while 92 and 99% of correct classification were obtained using MIR and NIR spectra data, respectively. As for the prediction of the purity level of EVAO, partial least square regression applied on FFFS, MIR, and NIR spectra data allowed to obtain an excellent prediction of adulteration level, since R 2 of 0.99, 0.99 and 0.98 were calculated, respectively.