This study presents a statistically optimized protocol for the green synthesis of gold nanoparticles (Au NPs) using aqueous Kalanchoe pinnata leaf extract (AKPLE). An integrated experimental strategy, transitioning from preliminary one-factor-at-a-time (OFAT) screening to a five-factor Box–Behnken Design, was employed to model and simultaneously optimize two critical optical responses derived from surface plasmon resonance: the peak position (λ_max) and its absorbance intensity. Highly predictive quadratic models (R² > 0.97) revealed that synthesis outcomes are governed by significant nonlinear curvature, with minimal interaction effects. Multi-response optimization via a desirability function identified a harmonized set of conditions (HAuCl₄: 0.44 mM, AKPLE: 3.50% v/v, temperature: 80.6 °C, pH: 7.2, time: 66.7 min) predicted to minimize λ_max at 540 nm while maximizing absorbance to 0.61. Synthesis under these optimized conditions successfully produced spherical, crystalline Au NPs, as confirmed by characterization (average TEM size: 26.3 ± 4.1 nm; zeta potential: –30.45 mV). This work demonstrates that a hybrid OFAT-RSM approach is superior for the precise, multivariate optimization of plant-mediated Au NP synthesis, providing a validated and scalable framework to balance nanoparticle size and plasmonic intensity—an outcome unattainable through conventional OFAT methods.