The relationship degree between money supply and inflation is one of the important element in macroeconomic policy as governments try to control inflation. In this study, this relationship and its inflation forecasting potential is investigated for the Turkish Economy. The multilayer perceptron neural network model is constructed for the monthly data set from 1996:2 to 2006:1. Broad money supply plus foreign demand deposits (M2Y), seasonal dummy, time trend dummy and previous inflation (auto-regressive term) are used as input variables and inflation is used as output variable of the model. Sensitivity analysis is applied to discover the cause and effect relationship between input and output variables. Results show that the model predicts the level of the inflation with a reasonably good degree of accuracy.