Aiming at the disadvantages of prediction model of single BP neural network, a prediction model was presented by combining AdaBoost algorithm and BP neural network for improving the forecasting accuracy of single BP neural network. The ensemble BP network based on AdaBoost is used as intelligent algorithm. Overcoming the instability of single BP neural network, the proposed models can give more accurate and stable prediction for the novel conditions. The main influence factors for prediction of market demand of refrigerator are analyzing detailed and used as the inputs of proposed prediction model. The efficiency of the proposed prediction model was tested by simulation of the market demand statistical data of a refrigerator enterprise in China. The simulation results have shown that the higher accuracy is expressed in this proposed model, and it is applicable to practice. analyzing detailed and used as the inputs of proposed prediction model. The efficiency of the proposed prediction model was tested by simulation of the market demand statistical data of a refrigerator enterprise in China. The simulation results have shown that the higher accuracy is expressed in this proposed model, and it is applicable to practice.