The growing demand for efficient, selective, and stable enzymes has fueled advancements in computational enzyme engineering, a field that complements experimental methods to accelerate enzyme discovery. With a plethora of software and tools available, researchers from different disciplines often face challenges in selecting the most suitable method that meets their requirements and available starting data. This review categorizes the computational tools available for enzyme engineering based on their capacity to enhance the following specific biocatalytic properties of biotechnological interest: (i) protein-ligand affinity/selectivity, (ii) catalytic efficiency, (iii) thermostability, and (iv) solubility for recombinant enzyme production. By aligning tools with their respective scoring functions, we aim to guide researchers, particularly those new to computational methods, in selecting the appropriate software for the design of protein engineering campaigns. De novo enzyme design, involving the creation of novel proteins, is beyond this review's scope. Instead, we focus on practical strategies for fine-tuning enzymatic performance within an established reference framework of natural proteins.