The conventional method of medium optimization is one factor at a time (OFAT); time consumption and absence of factors interaction are the main drawbacks. To address this problem, Box and colleagues developed software called Response Surface Methodology (RSM), which comprises different models of designs for medium optimization. Design of Experiment (DOE) consists of different optimization models, commonly used models are Box-Behnken Design (BBD), Central Composite Design (CCD), and Artificial Neuron Network (ANN). These models are founded on the domain, matrix, variables, and responses. Each stage of design can be evaluated by different tools to find out the most influenced factors for the significant scale up of production. Many microbial species are sources of a wide spectrum of bioactive molecule production with considerable applications. Amongst the diverse microbial groups, the Phylum Actinobacteria shares common properties with both bacteria and fungi and is reported to have the bulk share of commercial biomolecules. The commercially available microbial products within Actinomycetes are predominantly from Streptomyces sp. The optimization studies using RSM gained much attention in fermentation using Actinobacteria for reducing time and enhancing production. This review paper explores the application of Design of Experiment (DOE) for the discovery of different metabolites from Actinobacteria, its applications and medium optimization for enhanced production of these biomolecules using different models.