Futures prices forecasting plays a crucial role in business strategy. Numerous investigating addressing this problem have generally focussed on statistical methods, such as regression or ARIMA. However, traditional forecasting methods suffer from some deficiencies and limitations which make them severely inadequate for strategic planning in today's open market environment. In this paper FNN, namely an intelligent pricing forecaster, is basically a multi-layered fuzzy rule-based neural network which integrates the basic elements and functions of a traditional fuzzy logic inference into neural network structure. Model evaluation results for the price-forecasting performance of futures markets for live hogs and cattle indicate that the FNN model can perform more accurately than the conventional statistical models.