A model catalog is a centralized repository or registry where organizations track, manage, and serve their trained AI models. It records metadata like model version, training data used, performance metrics, deployment status, and lineage. Platforms like MLflow, Weights & Biases, and Hugging Face Hub provide model catalog functionality. A model catalog is essential for governance: it ensures teams know which model version is deployed in production and can roll back if needed.