This paper grasps the constant changes current situation of port container terminals with limited storage capacity with increasing container traffic volume and suggests the necessity of estimating loading and unloading operation time considering container yard. For this purpose, the actual terminal data was divided into general total volume information and yard location information. As a result of analysis by model, the artificial neural network model with the yard location information was the highest. In the future, it is expected to contribute to the improvement of container terminal operation efficiency by suggesting the loading and unloading time estimation considering the yard location information.