A method and system for wastewater treatment based on dissolved oxygen control by a fuzzy neural network, the method for wastewater treatment comprising the following steps: (1) measuring art inlet water flow rate, an ORP value in an anaerobic tank, a DO value in an aerobic tank, an inlet water COD value, and an actual outlet water COD value; (2) collecting the measured sample data and sending them via a computer to a COD fuzzy neural network predictive model, so as to establish an outlet water COD predicted value, (3) comparing the outlet COD predicted value with the outlet water COD set value, so as to obtain an error and an error change rate, and using them as two input variables to adjust a suitable dissolved oxygen concentration. Accordingly, the on-line prediction and real-time control of dissolved oxygen wastewater treatment are achieved. The accurate control of dissolved oxygen concentration by the present method for wastewater treatment can achieve a saving in energy consumption while ensuring stable running of the sewage treatment system, and the outlet water quality meets the national emission standards.