The aim of this paper is to forecast passenger numbers and freight volumes in 2005 and it is proposed optimal tonnage of passenger ship. The forecasting of passenger numbers and freight volumes is important problem in order to determine optimal tonnage of passenger ship, port plan and development. In this paper, the forecasting of passenger numbers and freight volumes are performed by the method of neural network using back-propagation learning algorithm. And this paper compares the forecasting performance of neural networks with moving average method and exponential smooth method As the result of analysis. The forecasting of passenger numbers and freight volumes is that the neural networks performed better than moving average method and exponential smoothing method on the basis of MSE(mean square error) and MAE(mean absolute error).