New advances in machine learning combined with cell-free protein synthesis are creating synergistic capabilities to expedite enzyme evolution. Machine learning models guide the design of enzyme variants by predicting the impact of amino acid changes on enzyme function. Cell-free protein synthesis enables rapid production and screening of these variants, facilitating high-throughput experimentation. By leveraging these technologies, innovators and researchers can now efficiently evolve enzymes with desired properties in a cost-effective and accelerated manner. This integrated approach represents a powerful tool for advancing biocatalysis and enzyme engineering within the realm of synthetic biology and bioengineering.