Biofabrication, broadly described as “a process that results in a defined product with biological function,” has undergone a revolution in recent years. This revolution has led to an explosion of literature containing valuable data and insights on bioactive materials and machine learning-aided design. However, the accessibility and comprehension of this rich data source remain a challenge, necessitating the creation of a comprehensive database. Herein, we present the manufacturing multi-organs database (MMDB), a real-time updating database developed to foster an all-inclusive understanding of biofabrication by leveraging machine learning for standardized analysis of material properties and manufacturing processes. The MMDB aids in identifying commonly used cells, materials, and culture strategies in biofabrication by analyzing over 5000 papers related to 37 human organs. Leveraging machine learning models, it predicts optimal printing parameters and organ functionality metrics, thereby streamlining experimental designs and reducing costs. In addition, MMDB offers knowledge services that encompass hotspot analysis, trend identification, international collaboration analysis, and comprehensive knowledge maps of organ functions and biomaterials. We believe that the MMDB, serving as a crucial and readily accessible knowledge base, will fundamentally facilitate the design and optimization of biofabrication experiments. Moreover, by accelerating the discovery of optimal parameters, the MMDB has the potential to offer invaluable insights into organ function, propelling the field of biofabrication toward more efficient and effective organ manufacturing.