In this paper, we address the asymptotic stability problem for the fractional-order neural networks system with uncertainty based on sampled-data control. First, considering the influence of uncertainty and fractional-order on the system, a new sampled-data control scheme with variable sampling period is designed. According to the input delay approach, the dynamics of the considered fractional-order system is modeled by a delay system. The main purpose of the problem addressed is to design a sampled-data controller, such that the closed-loop fractional-order system can guarantee the asymptotic stability. Then, the fractional-order Razumishin theorem and linear matrix inequalities (LMIs) are used to derive the stable conditions. The new delay-dependent and order-dependent stability conditions are presented in the form of LMIs. Furthermore, the sampling controller can be obtained to ensure the stability and stabilization of fractional-order system. Finally, a numerical example is given to demonstrate the effectiveness and advantages of the proposed method.