eng International Academy of Ecology and Environmental Sciences Computational Ecology and Software 2220-721X 2026-3-1 16 1 58 98 3 article WenJun Zhang 1 2 International Academy of Ecology and Environmental Sciences, Hong Kong, China; School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China In present study a system of hierarchical indicators to assess animal species' adaptation to climate change was constructed, and the AI-driven assessment tool was developed. It is a single-page web tool that: (1) Collects species and context information from the user. (2) Lets the user choose an AI provider (DeepSeek or Google Gemini) and enter an API key. (3) Builds a detailed prompt requesting a JSON-formatted climate adaptation assessment. (4) Sends the prompt to the selected provider's REST API. (5) Parses and validates the JSON-like response. (6) Renders the results into a rich UI, grouped into: Physiological indicators, Morphological indicators, Behavioral indicators, Genetic indicators, Summary assessment and conservation recommendations. With this AI tool, we can easily judge the real-time vulnerability of the given animal species to climate change and obtain conservation recommendations. http://www.iaees.org/publications/journals/ces/articles/2026-16(1)/AI-driven-assessment-of-animal-adaptation-to-climate-change.pdf animal adaptation climate change AI assessment web tool