A method of statistical neurodynamics is presented for treating ensembles of nets of randomly connected neuron-like elements. The concept of a macrostate plays a fundamental role in statistical neurodynamics and a criterion is given for ascertaining that given macroscopic quantities together constitute a macrostate. The activity of a nerve net is shown to be a macrostate and the equation of the dynamics of the activity is elucidated for various ensembles of random nerve nets. It is shown that the distance between two microstates can also be treated as a macrostate in a generalized sense. The equation of its dynamics represents how the distance between two states changes in the course of state transitions. The dynamics of distance reveals interesting microscopic properties of random nerve nets, such as the stability of state-transition, the transient lengths, etc.