The aim of this paper was to evaluate the potential of using near-infrared (NIR) spectroscopy and multivariate analysis as a rapid tool to non-destructively determine the presence of surface treatments applied to cork stoppers. Density and dimensions of 6 closure varieties were characterized and the extraction force was measured on those produced for still wines. Cork stoppers were also analyzed using hand-held NIR and Raman spectrometers. Soft independent modelling of class analogy (SIMCA) models showed significant differences among treated and untreated samples, linked to components of the coating agents applied (silicone and paraffin). SIMCA model's classification performance was tested and high sensitivity (93.33 %) and specificity (100 %) values were obtained. Partial least squares regression (PLSR) model accurately predicted the extraction forces measured with low standard error of prediction (SEP = 4.0 daN). Our results are promising for the future application of this technology in cork industry, reducing time and economic losses.