Nine different types of Italian red wines of four different varieties were analysed, without any sample pre-treatments, by voltammetric techniques using a poly(3,4-ethylenedioxythiophene)-modified electrode. The data matrices consisting of the currents measured at different potentials, by repeated Cyclic Voltammetry or Differential Pulse Voltammetry, are submitted to chemometric analysis. After explorative tests based on Principal Component Analysis, Partial Least Squares-Discriminant Analysis classification models are built both for the training and for the test sets. To this aim, different classification strategies are adopted, considering the responses from the two techniques either separately or joined together to form a data matrix including the whole voltammetric information.