This　paper　is　concerned　with　antisynchronization　in　predefined　time　for　two　different　chaotic　neural　networks.　Firstly,　a　predefined-time　stability　theorem　based　on　Lyapunov　function　is　proposed.　With　the　help　of　the　definition　of　predefined　time,　it　is　convenient　to　establish　a　direct　relationship　between　the　tuning　gain　of　the　system　and　the　fixed　stabilization　time.　Then,　the　antisynchronization　is　achieved　between　two　different　chaotic　neural　networks　via　active　control　Lyapunov　function　design.　The　designed　controller　presents　the　practical　advantage　that　the　least　upper　bound　for　the　settling　time　can　be　explicitly　defined　during　the　control　design.　With　the　help　of　the　designed　controller,　the　antisynchronization　errors　converge　within　a　predefined-time　period.　Numerical　simulations　are　presented　in　order　to　show　the　reliability　of　the　proposed　method.