This study proposes a multi-hierarchical classification method for marine organisms. Marine organisms are diverse, and organisms of the same phylum have strong inter-class similarity, while organisms of various phyla have large differences. Meanwhile, a multi-hierarchical classification method is designed by utilizing the similarity among species to help the network learn biological prior knowledge. Additionally, this study designs a C-MBConv module and improves the EfficientNetV2 network architecture by combining the multi-hierarchical classification method, and the improved network architecture is called CM-EfficientNetV2. The experiments show that CM-EfficientNetV2 has higher accuracy than the original network EfficientNetV2, with an accuracy improvement of 1.5% on the inter-tidal marine biology dataset of the Nanji Islands and 2% on CIFAR-100.