The sensory attributes of extra virgin olive oil, and in particular specific aroma defects, are officially responsible for oil classification (or declassification) into extra virgin, virgin or lampante olive oil. Undoubtedly, volatile compounds play a crucial role in defining olive oil sensory quality and research efforts have been dedicated to unravel the composition of this informative fraction, to better understand correlations with quality attributes. The relative distribution of volatiles depends on several parameters (i.e., cultivar, geographical origin, fruit ripeness, processing practices, and storage) meaning the identification of an unequivocal fingerprint correlated to quality and authenticity is a difficult task. Most of these variables contribute towards the intensity and quality of the green and fruity perception, while the presence of defects is mainly due to inappropriate manufacturing practices. Multiple-cumulative trapping headspace-solid-phase microextraction (named MC-SPME) is a powerful technique proven to enhance the level of information on the volatile profile. Shorter cumulative extraction times, using a low volume of sample to avoid headspace saturation proved effective for discriminating between different qualities of olive oil (i.e. extra-virgin, virgin and lampante oil) as well as the different geographical origins among the extra virgin oils. The use of a novel data mining and chemometrics software enabled automatic alignment of chromatograms and extraction of useful information in a simple and straightforward way, supporting the routine application of this approach to corroborate sensory panel analysis.