The application of sodium cyanide for gold leaching remains the predomnant method for gold extraction. However, the efficiency of the gold leaching process depends on several interacting per-formance variables, including cyanide concentration, pH, pulp density, particle size, leaching time, dissolved oxygen, agitation rate, and temperature. The combined influence of perfor-mance variables on gold recovery has not been fully optimized. Therefore, a quantitative assessment is required to understand their relational strength effects. A literature review identified eight key performance variables commonly monitored in gold leaching operations, both with and without pretreatment methods. The effects of performance variables on gold recovery were evaluated using grey relational analysis and the coefficient of variation. Artificial intelligence, particularly artificial neural networks integrated with statistical methods, was also explored to predict the effects of variables on strength and gold recovery efficiency. The analysis produced mean relational degrees of 0.59 and 0.54, with coefficients of variation of 9.0% and 10.8% for processes without and with pretreatment methods, respectively. The relational degree indicated moderate variability across the datasets. The findings confirm that input performance variables strongly influence gold leaching efficiency. The dosage ranges identified in this study can serve as valuable benchmarks for op-timizing gold recovery in industrial leaching operations.