Achieving a good level of resilience to extreme events caused by severe weather conditions is a major target for operators in modern power systems due to the increasing frequency and intensity of extreme weather phenomena. Moreover, regulatory authorities are pushing transmission and distribution operators to prepare resilience plans suitably supported by Cost–Benefit Analyses (CBAs). In this context, this paper proposes a CBA framework based on Optimization via Simulation (OvS) for the selection of the optimal portfolio of resilience enhancement measures. Starting from a comprehensive set of candidate grid hardening and operational measures, the optimal mix is identified by applying a novel two-step procedure based on an efficient application of the generalized pattern search heuristic technique. Risk indicators for the CBA are quantified, accounting for probabilistic models of climate changes. Moreover, the potential cascading outages due to multiple component failures provoked by extreme events are simulated on selected scenarios. The examples carried out on an IEEE test system show the effectiveness of the approach in identifying the best portfolio of resilience enhancement measures depending on climate change projections and costs of the measures, while the application to the model of a large portion of the Italian EHV transmission system demonstrates the practicability of the approach in real-world studies to support operators in different power system management phases, from planning to operation.