The stability of serine proteases is of major importance for their application in industrial processes. Here we study the determinants of the stability of a Nocardiopsis prasina serine protease using fast residual activity assays, a feature classification algorithm, and structure-based energy calculation algorithms for 121 micropurified mutant enzyme clones containing multiple point mutations. Using a multivariate regression analysis, we deconvolute the data for the mutant clones and find that mutations of residues Asn47 and Pro124 are deleterious to the stability of the enzyme. Both of these residues are situated in loops that are known to be important for the stability of the highly homologous α-lytic protease. Structure-based energy calculations with PEATSA give a good general agreement with the trend of experimentally measured values but also identify a number of clones that the algorithm fails to predict correctly. We discuss the significance of the results in relation to the structure and function of closely related proteases, comment on the optimal experimental design when performing high-throughput experiments for characterizing the determinants of protein stability, and discuss the performance of structure-based energy calculations with complex data sets such as the one presented here.