Events of the past few years have shown how today’s modern technological society is critically dependent on critical infrastructure networks such as telecommunications, transport and power. In this chapter, we examine the robustness of critical infrastructure networks and describe some simulation studies exploring this issue. These studies use an extension of data farming we call “network farming,” implemented within the CAVALIER network analysis tool suite. We then survey some historical data on actual terrorist attacks and show that the distribution of these attacks in time can be modeled by a Poisson statistical distribution. This fact can then be used to plan robust network architectures. We alsoexamine “scale-free networks,” and show how they relate to the robustness of physical and organizational networks. In particular, we study the implications for law-enforcement personnel responding to terrorist organizations, using two historical case studies. Finally, we briefly survey emerging trends in network modeling and intelligent software agents that may influence the robustness of future networks.