The present study investigated the effect of malaxation times (Mt: 0, 15, 30, 45 and 60 min), during the industrial extraction of cv. Arbequina oils at 25 ºC on total phenolic content and bitterness index of olive pastes. Additionally, the possibility of applying a lab-made potentiometric electronic tongue (E-tongue), comprising 40 lipid/polymer sensor membranes with cross sensitivity, to discriminate the olive pastes according to the Mt, was evaluated. The results pointed out that the olive pastes’ total phenolic contents significantly decreased (P-value < 0.001, one-way ANOVA) with the increase of the Mt (from 2.21±0.02 to 1.99±0.03 g GAE/kg olive paste), being observed a linear decreasing trend (R-Pearson = -0.910). Similarly, the bitterness index also decreased with the Mt (23.4±0.3 to 21.9±0.4 oleuropein/kg olive paste). These findings may be tentatively attributed to the migration of the phenolic compounds from the olive pastes to the extracted oil and water phases, during the malaxation process. Finally, the E-tongue signals, acquired during the analysis of the olive pastes’ methanolic extracts (methanol:water, 80:20 v/v), together with a linear discriminant analysis (LDA), coupled with a simulated annealing (SA) algorithm, allowed to establish a successful classification model. The E-tongue-LDA-SA model, based on 11 selected non-redundant sensors, allowed to correctly discriminate all the studied olive pastes according to the Mt (sensitivities of 100% for training and leave-one-out cross-validation). The satisfactory performance of E-tongue could be tentatively explained by the known capability of lipid/polymeric sensor membranes to interact with phenolic compounds, through electrostatic interactions and/or hydrogen bonds, which total content depended on the Mt.