Designing and maintaining resilient and robust transportation systems requires identification of links that are critical for the functionality of the network. Traditional traffic simulations techniques create a large computational burden, especially for larger traffic networks. This talk presented the recently developed Link Criticality Index (LCI) which can provide transportation link criticality rankings for large networks with a single User Equilibrium (UE) traffic assignment. The LCI was tested on well-known large transportation test networks and compared with other criticality measures. The findings showed that LCI successfully provides balanced link criticality rankings with respect to network connectivity and redundancy as well as the network flow conditions. Due to elimination of link removals, the LCI runtime is considerably shorter than comparable traffic assignment based approaches, i.e., in the order of the number of links in the network. The inclusion of network topology and demand characteristics, and shorter runtime make the LCI an appealing approach for transportation link criticality analysis.