Recognizing the importance of enhancing yield in industrial fermentation processes, we aimed to optimize biomass and ethanol yields in  Saccharomyces Cerevisiae using Box-Behnken experimental design, a response surface methodology (RSM) approach. Traditional optimization through the one-variable-at-a-time (OVAT) approach is labor-intensive and often fails to achieve optimal outcomes due to unaccounted interactions between variables. Our study employed a statistically designed RSM approach to evaluate the effects of medium variables interactions for more efficient pathway for industrial enhancement. S. cerevisiae strain K88 (CEN.PK122) was used this study for ethanol production due to its and recognized industrial applications. The medium variables were yeast extract, ammonium sulphate, and yeast nitrogen base supplemented with the amino acids: histidine, methionine and tryptophan. Statistical analysis revealed that YNB and amino acid concentrations enforces biomass production and facilitates ethanol production through increased nitrogen uptake. The optimized biomass yield achieved was increased by 16% (to 0.59 g/g) , while the ethanol yield was much highly increased by 40% (to 0.42 g/g) over the basal medium. Optimal yield was attained at the following concentrations: yeast (9.4 g/L) extract, of ammonium sulfate (3.7 g/L) and of YNB (5.1 g/L) with amino acids. Surface plots represent the optimal amount for each variable in medium formulation. This study highlights the efficiency of Box-Behnken design in complex fermentation systems for industrial bioprocess applications.