The analysis and design of materials is often a slow process that may take weeks, months, or years, and many current material platforms rely on expensive raw material sources that fail to achieve sustainability goals. Meanwhile, bio-inspired Materials Informatics—fueled by emerging techniques such as multiscale modeling, machine learning, and autonomous experimentation—is transforming the way materials are understood, discovered, developed, and selected. The impact of these tools is particularly noteworthy since they can be used to develop materials with fewer resources and with greater societal impact. A field that would strongly benefit from the use of Materials Informatics tools is that of structural biological materials, where mechanical properties are crucial for biological and engineering properties for species survival such as fracture-resistant armor against predators, elastic recovery for repeated loadings, or mechanical actuation capacity. Generations of researchers have studied biological materials for their fascinating structure–property relationships that make up their impressive properties, including mechanical resilience. Despite the accumulation of scientific knowledge, relatively little has been translated to generating engineered bio-inspired materials. Addressing this gap, emerging Materials Informatics tools can now be used to make use of legacy data, newly collected empirical observations, and predictive models to make significant advances in this field.