A method for the on-line prediction of the driving cycle in a circulating automotive vehicle, the driving cycle being the vehicle speed as a function of time, characterized in that it comprises: - a step of data pre-processing, which in turn comprises: • receiving the vehicle speed (V sp); • receiving traffic information corresponding to the expected path for the vehicle within at least one prediction horizon considered; • obtaining a reference driving cycle (V pat) corresponding to the expected path within at least said prediction horizon from the traffic information received; • calculating the deviation ( DV sp) of the vehicle speed (V sp) with respect to the reference driving cycle (V pat); - a step of data processing by means of a neural network, which comprises recursively obtaining the expected deviations ( D*V sp) for the prediction horizon, using for that purpose the deviations of speed ( NN_DV sp) previously calculated and corresponding to the recent past, defined by the delay sample number as well as information relating to the reference driving cycle ( NN_V pat) containing information belonging both to the recent past, defined by the delay sample number, and to the near future, defined by the future sample number, as inputs of the neural network; - a step of data post-processing which comprises obtaining the estimated speed (V* sp) for said prediction horizon from the expected deviations (D*V sp) and the reference driving cycle (V pat) for the prediction horizon. - a step of data pre-processing, which in turn comprises: • receiving the vehicle speed (V sp); • receiving traffic information corresponding to the expected path for the vehicle within at least one prediction horizon considered; • obtaining a reference driving cycle (V pat) corresponding to the expected path within at least said prediction horizon from the traffic information received; • calculating the deviation ( DV sp) of the vehicle speed (V sp) with respect to the reference driving cycle (V pat); • receiving the vehicle speed (V sp); • receiving traffic information corresponding to the expected path for the vehicle within at least one prediction horizon considered; • obtaining a reference driving cycle (V pat) corresponding to the expected path within at least said prediction horizon from the traffic information received; • calculating the deviation ( DV sp) of the vehicle speed (V sp) with respect to the reference driving cycle (V pat); - a step of data processing by means of a neural network, which comprises recursively obtaining the expected deviations ( D*V sp) for the prediction horizon, using for that purpose the deviations of speed ( NN_DV sp) previously calculated and corresponding to the recent past, defined by the delay sample number as well as information relating to the reference driving cycle ( NN_V pat) containing information belonging both to the recent past, defined by the delay sample number, and to the near future, defined by the future sample number, as inputs of the neural network; - a step of data post-processing which comprises obtaining the estimated speed (V* sp) for said prediction horizon from the expected deviations (D*V sp) and the reference driving cycle (V pat) for the prediction horizon.