Freight rail networks serve an essential role in transporting goods to accommodate marketdynamic demands and public needs, and subsequently network analyses of such systems become of importance for providing insights into enhancing transportation efficiency and resilience. This thesis develops and investigates a topological analysis model termed as connectedness efficiency, which is associated with the connectedness of a network’s nodes by its links and corresponding attributes. Analysis outcomes from such a model can be utilized for providing economical insights on the network’s performance. This model can be used to analyze network topologies without assigning weights to their nodes and links, or with weight assignments to nodes and links based on different attributes, such as volumes of goods handled at nodes, physical-length of links, commodity volume transported through links, and travel fuel cost through links. Such an analysis can be utilized for: (1) defining distinctions that may be employed for the assignment of node and link weights, (2) gaining understanding of node and link criticality, and (3) providing methods for objectively maintaining and enhancing network performance. This analysis informs decisions to be considered by rail managers and executives in financial management, planning expansions, route changes, or preparations for potential node or link failures. A case study using an aggregate U.S. freight railroad network along with other example topologies is presented to examine different network attributes as well as their influence on connectedness efficiency and loss impacts of nodes and links.