Characterisation of coffees according to their origins is of utmost importance for commercial qualification. In this study, the aroma profiles of different batches of three monoorigin roasted Coffea arabica coffees (Brazil, Ethiopia and Guatemala) were analysed by Proton‐Transfer‐Reaction‐Time of Flight‐Mass Spectrometry (PTR‐ToF‐MS). The measurements were performed with the aid of a multipurpose autosampler. Unsupervised and supervised multivariate data analysis techniques were applied in order to visualise data and classify the coffees according to origin. Significant differences were found in volatile profiles of coffees. Principal component analysis allowed visualising a separation of the three coffees according to geographic origin and further partial least square regression‐discriminant analysis classification showed completely correct predictions. Remarkably, the samples of one batch could be used as training set to predict geographic origin of the samples of the other batch, suggesting the possibility to predict further batches in coffee production by means of the same approach. Tentative identification of mass peaks aided characterisation of aroma fractions. Classification pinpointed some volatile compounds important for discrimination of coffees. Copyright © 2014 John Wiley & Sons, Ltd.