The aim of this dissertation is to provide a set of results in stability, perfor- mance, and robustness of model-based networked control systems with intermit- tent feedback, which will serve as a nexus between the study of systems with instantaneous feedback and with continuous feedback. We apply the concept of Intermittent Feedback to a class of networked control systems known as Model-Based Networked Control Systems (MB-NCS). Model- Based Networked Control Systems use an explicit model of the plant in order to reduce the network traÌâå±c while preserving performance specifications, while In- termittent Feedback consists of the loop remaining closed for some fixed interval, then open for another interval. We begin by introducing the basic architecture for model-based control, then discuss the concept of intermittent feedback, its applica- tions in various fields, and its role as a link between instantaneous and continuous feedback. We then provide stability results for the model-based architecture with intermittent feedback. We also address the case with output feedback (through the use of a state observer), providing a full description of the state response of the system, as well as a necessary and sufficient condition for stability in each case. Extensions of our results to cases with nonlinear plants are also presented. Next, we investigate the situation where the update times tau and h are time-varying, first addressing the case where they have upper and lower bounds, then moving on to the case where their distributions are i.i.d or driven by a Markov chain. We then study the case of model-based control with intermittent feedback for discrete-time plants, again providing stability conditions for the basic architecture, the state observer case, and the case with time-varying parameters. Next, we shift our attention from stability to other aspects of model-based NCS with intermittent feedback, such as performance and robustness. Finally, we provide conclusions and propose research directions through which this work could be expanded upon in the future.