Introduction. The aim of this study was to determine the ability of anelectronic nose (e-nose) to predict the quality of nectarines and peaches, and, inparticular, the aroma. Materials and methods. Four nectarine cultivars(‘María Dolce’, ‘Maillarlate’, ‘Nectaross’ and ‘Venus’) and one peach cultivar (‘RoyalGlory’) were evaluated. The fruit was harvested ripe and the quality evaluations werecarried out just one day after harvest. The intensity of the main descriptors of fruitquality was described, and fruits were subjected to an e-nose assessment. The sensoryanalysis and the e-nose results were presented through a Principal Component Analysis(PCA). A multiple linear regression (MLR) was also used to create a predictive model forthe attribute ‘aroma’ compared with the other sensory parameters and the most informativee-nose sensor data. Results and discussion. ‘Royal Glory’ and ‘María Dolce’were placed in a separate cluster far from ‘Venus’, ‘Nectaross’ and ‘Maillarlate’. Theresult of the MLR included the attributes ‘acidity’, ‘sweetness’ and ‘acceptability’ inthe model, and the data registered by sensor 6 of the e-nose (SnO2-sensor, RGTO Mo, 45 Åthick layer), which were those factors that best related to the aroma, reached aR 2 of 0.48 and a mean square error (MSE) of 3.85. It wasconcluded that the e-nose is an instrument able to discriminate peach varieties throughtheir aromatic features, which are among the descriptors that mainly determineacceptability by the peach consumer.