This thesis investigated the application of stochastic ground motion models for characterization of seismic hazard within the context of life-cycle cost assessment for earthquake engineering applications. A versatile, simulation-based, framework was adopted for assessment of the life-cycle repair cost and for the identifications of the importance of the risk factors related to the seismic hazard description. Two different stochastic ground motion models were considered a source-based one [GM1] (Atkinson and Silva 2000) and a record-based one [GM2] (Rezaeian and Der Kiureghian 2010). These models are formulated by modulating a high-dimensional stochastic sequence through functions that address spectral and temporal characteristics of the excitation. The parameters of these models are connected to the regional seismicity characteristics through predictive relationships. Description of the uncertainty for these characteristics and for the predictive relationships, by appropriate probability models, leads then to a complete description of seismic hazard, expressed in terms of ground-motion time-history. An assembly-based vulnerability approach was adopted in this setting to quantify earthquake losses based on the nonlinear time-history structural response. Life-cycle repair cost was quantified by its expected value over the space of the uncertain parameters for (each) excitation model considered and estimation of this expected value through stochastic simulation was adopted. An efficient probabilistic sensitivity analysis was also discussed, based on advanced stochastic sampling concepts. This analysis aims to identify the importance of the various uncertain parameters within the seismic hazard description (i.e., risk factors) in the overall performance of the structural system as well as potential correlations between them. This methodology is based on the definition of an auxiliary density function, proportional to the integrand of the expected cost integral, and on the comparison of this density to the initial probability models through their relative information entropy. The framework was illustrated through application to a four-storey concrete building. Results were presented with respect to the total cost as well as with respect to the cost of different damageable assemblies. The influence of the installation of viscous dampers to the structure on the life-cycle repair cost was also considered.