Optimizing adsorption performance is a complex task due to the interplay of these variables and the diversity of PFAS compounds, which vary in molecular weight, chain length, hydrophobicity, and functional groups. Traditional experimental approaches, such as one-factor-at-a-time (OFAT) studies, are insufficient for capturing multidimensional interactions between variables and require extensive time and resources. To overcome these challenges, advanced statistical and computational methods are essential for systematically modeling and optimizing adsorption systems.