This set of slides was presented at the CNLS Smart Grid Seminar Series at Los Alamos National Lab on Feb 2, 2010. Random Matrix Theory is useful in the study of complex networks such as electric grids. These transmission systems can be modeled as complex networks, with high-voltage lines the edges that connect nodes representing power plants and substations. This presentation draws upon established literature of complex systems theory and introduce new methods from nuclear and statistical physics to identify new characteristics of these networks. It shows that most grids can be characterized by the Gaussian Orthogonal Ensemble, an indicator of chaos in many complex systems. Under certain circumstances, however, grids may be described by Poisson statistics, an indicator of regularity.