<p>This article investigates the adaptive neural network predefined-time consensus control problem for fractional-order multiagent systems (MASs) with output constraints. Due to the unknown nonlinear dynamics and unmeasurable states in fractional-order MASs, neural networks are employed to identify the unknown nonlinear functions, and the neural network state observers are designed to estimate the unmeasurable states. In addition, a predefined-time stabilization criterion for fractional-order MASs is introduced. The barrier Lyapunov function is introduced to address the output constraint problem, and an event-triggered mechanism with a switching threshold is proposed to conserve communication resources. Then, by combining the fractional-order dynamic surface control design approach with predefined-time theory, an adaptive predefined-time control scheme based on event-triggered control is proposed. Finally, it is demonstrated that the controlled system achieves semi-global practical predefined-time stability (SGPPTS), with all signals remaining bounded. The effectiveness of the proposed theory and method is demonstrated through simulation results.</p>