Our earlier work established a contention-resolving model predictive control (or MPC) framework to co-design priorities and control for networked control systems (or NCSs), assuming the system models are perfect. However, due to the differences between a model and the real world, there are inevitable perturbations. In this paper, we focus on perturbations of the predicted timings, which are rarely addressed in the literature, and present a robust MPC de-sign to achieve guaranteed performance under such timing perturbations. We propose a state-feedback correction term with dynamic gain, added to the nominal contention-resolving MPC policy, which can eliminate the state deviation between perturbed and nominal systems at the predicted task completion time. Additionally, we identified the largest tolerable timing perturbation for such a robust MPC design. Under the tolerable timing perturbations, we analytically proved that the state deviation can be bounded by a forward invariant set (or FIS) for all time. The robust MPC policy can be then designed based on the FIS, such that perturbed system trajectories are guaranteed to satisfy all the original state and control constraints. The effectiveness of our proposed method is verified through simulation.