The present paper discusses response surface methodology as an efficient approach for predictive model building and optimization of As(V) adsorption on activated carbon derived from a food industry waste: peach stones. The objectives of the study are application of a three-factor 23 full factorial and central composite design technique for maximizing As(V) removal by produced activated carbon, and examination of the interactive effects of three independent variables (i.e., solution pH, temperature, and initial concentration) on As(V) adsorption capacity. Adsorption equilibrium was investigated by using Langmuir, Freundlich, and Dubinin-Radushkevich isotherm models. First-order and second-order kinetic equations were used for modeling of adsorption kinetics. Thermodynamic parameters (ΔG °, ΔH °, and ΔS °) were calculated and used to explain the As(V) adsorption mechanism. The negative value of ΔH (−7.778 kJ mol−1) supported the exothermic nature of the sorption process and the Gibbs free energy values (ΔG°) were found to be negative, which indicates that the As(V) adsorption is feasible and spontaneous.