The scaffold stimulates tissue regeneration and the development of new tissue by providing the right biochemical and biophysical indications to assist cell attachment and growth. The process of electrospinning has the potential to yield highly promising scaffolds for tissue engineering. The underlying relationship between the scaffold’s exceptional functional qualities, architecture, mechanical attributes, and process parameters is still not fully comprehended. The incomplete insights provided by the fragmentary results of several parametric studies can lead to an inadequate understanding of the function of parameter interactions. In order to close this gap, statistical techniques like the design of experiments (DOE) can be used to quantitatively identify correlations between important scaffold properties and control parameters in a methodical, comprehensive, and systematic way. Design of Experiments (DoE) is becoming more and more important in tissue engineering in the modern day. During formulation development, this method effectively screens and optimizes a multitude of experimental parameters using a simple experimental design. DoE seems to be quite helpful in that it requires fewer preliminary tests or trials while yielding the most information on the design. Nevertheless, because several important process parameters are involved and their optimization is inherently challenging, the majority of scaffold preparation to date has primarily depended on a trial-and-error methodology. Thus, the purpose of this research is to examine how DoE is applied to optimize properties of different kinds of nanoparticle based scaffolds. It also explores the topic of several scaffold types based on nanoparticles that have been created and optimized using DoE.