The increasing use of automated image capture in ecological and biodiversity studies has created a growing demand for efficient and practical tools for animal image classification. However, most existing methods treat the task as a simple object classification problem, which limits their utility for taxonomists and biologists. This paper presents a web-based application that integrates a hierarchical classification model with an interactive interface to support animal taxonomic research and public engagement. The core contributions are: (1) a multi-rank prediction framework that identifies six taxonomic ranks—species, genus, family, order, class, and phylum—from a single uploaded image, supported by bounding box localisation; (2) an evolutionary relationship comparison feature that determines the closest shared rank when two images are uploaded, enabling users to explore taxonomic proximity; and (3) a privacy-preserving design that automatically deletes user data after processing to ensure confidentiality. By bridging automated classification with taxonomic needs, this application offers a scalable tool for biodiversity conservation, research, and education.