Diet optimization is an important process to increase the efficiency of rearing insects and can be used to develop high-quality insects with specific fitness and life-history traits. Galleria mellonella (L.), the greater wax moth, is widely used in research, microbiology assays, as pet food, and host for biological control agents. Although artificial diets for G. mellonella have been researched and optimized for decades, preliminary tests indicated that the predominantly utilized G. mellonella diet could be improved to yield larger larvae with a short development time. We used a design of experiments (DOE) approach that incorporated multiple full factorial designs and a final mixture design to test the qualitative and quantitative effects of ingredients and their interactions on larval mass and survival. Analysis of 17 ingredient variations in 35 diet formulations yielded an optimized diet that supported high survival and 2.4-fold greater larval body mass than the standard rearing diet. This study demonstrates the importance and efficiency of statistical DOE in guiding the optimization of insect diets to improve traits that represent the quality and fitness of the reared insects.