Using quantitative analysis of intracellular metabolites is a valuable method for understanding biochemical processes in cellular systems. This study aimed to objectively evaluate various quenching–extraction techniques for intracellular metabolite profiling of Bacillus subtilis expressing serine alkaline protease (SAP) and to link metabolomics data with fermentation optimization. Among the tested methods (cold methanol, cold ethanol, and a mixture of acetonitrile and chloroform combined with fast filtration), cold methanol yielded the most efficient and reproducible extraction. Metabolomic analysis identified glucose 6-phosphate (G6P), fructose 6-phosphate (F6P), serine, and glycine as the most influential intracellular metabolites. Using the Box–Behnken design, different concentrations of the identified metabolites were systematically varied, and the model predicted optimal levels (G6P 0.52 mM, F6P 0.054 mM, serine 1.72 mM, glycine 0.07 mM) that enhanced SAP activity by nearly 300%, reaching 1530.33 U/mL compared to the control. These results establish a validated workflow that couples metabolomics with statistical methods to achieve enhanced protease production, offering both methodological and industrial relevance.