This paper compares two methods to predict inflation rates in Europe.One method uses a standard back propagation neural network and the other uses an evolutionary approach,where the network weights and the network architecture are evolved. Results indicate that back propagation produces superior results.However,the evolving network still produces reasonable results with the advantage that the experimental set-up is minimal.Also of interest is the fact that the Divisia measure of money is superior as a predictive tool over simple sum. This paper compares two methods to predict back inflation neural network and the other uses an evolutionary approach, where the network weights and the network architecture are evolved. Results indicate that back propagation produces superior results. , the evolving network still produces reasonable results with the advantage that the experimental set-up is minimal. Als of interest is the fact that the Divisia measure of money is superior as a predictive tool over simple sum.