The main purpose of this thesis is to apply simulation balancing to HappyGO and expect to find better results by adjusting the parameters, different training data and so on. HappyGO is one the Conputer GO program, and won silver of TAAI 9x9 Computer Go group. According to our experiments on simulation balancing, HappyGO with 500 playouts per move has a 9.3% win rate against Gnu GO 3.8 level 10 before training and raises to 48.7% after training.