Near ultraviolet spectroscopic fingerprints of Corsican honey samples were analysed by an array of chemometric tools in order to authorise their claimed origin. Genuine, unfiltered honeys (n= 373;219 Corsican and 154 non-Corsican) were gathered over the course of two production seasons, the principal goal was to create a particular spectral fingerprint for Corsican honey. After the preliminary data inspection by principal component analysis, the multivariate method analysed for provenance confirmed was partial least squares regression; numerous spectral pre-treatments were investigated. Best PLS discriminant models developed with the adoption of a full cross-validation, a variable selection algorithm and second derivative data pre-treatment gave correct classification results of 90.0% and 90.3% for Corsican and non-Corsican honey samples respectively. Using different calibration and validation samples from the honey collection, highest correct classification values of 90.4% and 86.3% for Corsican and non-Corsican honey samples respectively were acquired again using a variable selection procedure.