A force estimation method based on the surface electromyograph(sEMG) and generalized regression neural network (GRNN) is proposed for the demand of the force control of the intelligent EMG prosthetic hand. First, the experimental platform is introduced. The acquisition of the sEMG, the feature extraction of sEMG and the construction of GRNN are described. Then, the sEMG in the hand motions are detected by the EMG sensors with which eight different positions of arm skin surface are attached on. A three dimension force sensor is adopt to measure the force output by the human's hand. The multi channels of the sEMG and the force are measured synchronously. Characteristic matrix of the sEMG and the force signal are used to construct the GRNN. The mean square error is employed to assess the accuracy of the estimated force. Experiments are implemented to verify the effectiveness of the proposed estimation method. The experimental results show that the force output by the human's hand can be estimated by the used of sEMG and GRNN.