Multiphoton microscopy is the enabling tool for biomedical research, but the aberrations of biological tissues have limited its imaging performance. Adaptive optics (AO) has been developed to partially overcome aberration to restore imaging performance. For indirect AO, algorithm is the key to its successful implementation. Here, based on the fact that indirect AO has an analogy to the black-box optimization problem, we successfully apply the covariance matrix adaptation evolution strategy (CMA-ES) used in the latter, to indirect AO in multiphoton microscopy (MPM). Compared with the traditional genetic algorithm (GA), our algorithm has a greater improvement in convergence speed and convergence accuracy, which provides the possibility of realizing real-time dynamic aberration correction for deep in vivo biological tissues.