Nanosized spinel ferrites MFe2O4 (M = Ni, Co, and Zn) have been prepared by sol-gel autocombustion method using citric acid as a fuel agent. The materials are characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and transmission electron microscopy (TEM). The spinel ferrites have been applied for Congo-Red (CR) dye adsorption using batch technique. Different kinetic and equilibrium models have been fitted by nonlinear regression to analyze the adsorption data. In accordance with Langmuir isotherm, the maximum adsorption capacity at 293 K is 14.06 mg/g for CoFe2O4 and 17.13 mg/g for NiFe2O4. The values of mean free energy determined from Dubinin-Radushkevich isotherm are higher than 8 (kJ mol−1), indicating a chemisorption mechanism. Based on the calculated thermodynamic parameters (free energy, enthalpy, and entropy) the adsorption of CR onto ferrites is a spontaneous and endothermic process. Response surface methodology has been applied to construct the multiple regression models for prediction of the adsorption capacity and removal efficiency. The model-based optimization has been performed using genetic algorithms and desirability function approach. The single-objective optimization has yielded a maximum value of color removal efficiency of 98.995%, using NiFe2O4 adsorbent. The multiobjective optimization has resulted in the improvement of both removal efficiency and adsorption capacity.