Intelligent allocation and scheduling of airport security-check service resources is one of the effective ways to improve passenger service level and operational efficiency within the airport, while the accurately prediction about the security passenger traffic is the prerequisite for dynamic allocation and scheduling. This paper takes the historical passenger data at Tianjin airport security inspection as the research object, and puts forward a prediction method based on BP neural network so as to establish a prediction model of security-check passenger flow. Besides the proposed model by this paper is verified by the actual passenger flow of Tianjin airport, as we can know from the comparison results, the accuracy of the proposed algorithm can reach to above ninety percent, So the BP neural network prediction model behaves with higher forecasting accuracy, can be well applied to the security-check flow prediction in the airport terminal, which can support a high efficiency solution for the airport operators to dynamically allocate security-check services resources.