In this work, the fuzzy control was designed using genetic algorithm (GA) to control the temperature of a jacketed batch reactor in which styrene polymerization takes place under isothermal conditions. The fitness function for GA is chosen as the integral of the absolute value of the error (IAE). By using fuzzy parameters specified at constant temperatures, the efficiency of the fuzzy controller with GA was examined by simulation and experimentally. It was seen that GA is able to tune the fuzzy controller efficiently for different situations and therefore to control the temperature of the polymerization reactor.