This paper deals with the problem of non-fragile robust finite-time H-infinity control for a class of uncertain nonlinear stochastic Ito systems via neural network. First, applying multi-layer feedback neural networks, the nonlinearity is approximated by linear differential inclusion (LDI) under state-space representation. Then, a sufficient condition is proposed for the existence of non-fragile state feedback finite-time H-infinity controller in terms of matrix inequalities. Furthermore, the problem of non-fragile robust finite-time H-infinity control is reduced to the optimization problem involving linear matrix inequalities (LMIs), and the detailed solving algorithm is given for the restricted LMIs. Finally, an example is given to illustrate the effectiveness of the proposed method.