A hybrid intelligent technique is proposed to identify Bouc-Wen hysteresis model parameters. This intelligent technique is based on a hybrid of genetic algorithm (GA) and Levenberg–Marquardt algorithm (LMA). In the hybrid intelligent technique, the GA, a popular evolutionary optimization method, firstly searches the entire problem space to get a set of roughly estimated solutions. The LMA, a well-known numerical method, then performs a local optima search in order to carry out further optimizations. The performance of the hybrid intelligent technique is compared with GA method in terms of parameter accuracy. The simulation experiments of Bouc-Wen hysteresis model with known parameters are illustrated to show that a high quality solution can be achieved by means of the hybrid intelligent technique. The concept of hybrid intelligent technique may benefit the parameter identification in diverse hysteresis model problems.