Bridges play a key role in the transportation sector while serving as lifelines for the economy and safety of communities. The need for resilient bridges is especially important following natural disasters, where they serve as evacuation, aid, and supply routes to an affected area. Much of the earthquake engineering community is interested in improving the resiliency of bridges, and many contributions to the field have been made in the past decades, where a shift towards performancebased design (PBD) practices is underway. While the Canadian Highway Bridge Design Code (CHBDC) has implemented PBD as a requirement for the seismic design of lifeline and major route bridges, the nature of PBD techniques translate to a design process that is not universally compatible for all scenarios and hazards. Therefore, there is great benefit to be realised in the development of PBD guidelines for mainshock-aftershock seismic sequences for scenarios in which the chance to assess and repair a bridge is not possible following a recent mainshock. This research analytically explored a parameterized set of 20 reinforced concrete bridge piers which share several geometrical and material properties with typical bridge bents that support many Canadian bridges. Of those piers, half are designed using current PBD guidelines provided in the 2019 edition of the CHBDC, whereas the remaining half are designed with insufficient transverse reinforcement commonly found in the bridges designed pre-2000. To support this study, a nonlinear fiber-based modelling approach with a proposed material strength degradation scheme is developed using the OpenSEES finite element analysis software. A multiple conditional mean spectra (CMS) approach is used to select a suite of 50 mainshock-aftershock ground motion records for the selected site in Vancouver, British Columbia, which consist of crustal, inslab, and interface earthquakes that commonly occur in areas near the Cascadia Subduction zone. Nonlinear time history analysis is performed for mainshock-only and mainshock-aftershock excitations, and static pushover analysis is also performed in lateral and axial directions for the intact columns, as well as in their respective post-MS and post-AS damaged states. Using the resulting data, a framework for post-earthquake seismic capacity estimation of the bridge piers is developed using machine learning regression methods, where several candidate models are tuned using an exhaustive grid search algorithm approach and k-fold crossvalidation. The tuned models are fitted and evaluated against a test set of data to determine a single best performing model using a multiple scorer performance index as the metric. The resulting performance index suggests that the decision tree model is the most suitable regressor for capacity estimation due to this model exhibiting the highest accuracy as well as lowest residual error. Moreover, this study also assessed the fragility of the bridge piers subjected to mainshock-only and mainshock-aftershock earthquakes. Probabilistic seismic demand models (PSDMs) are derived for the columns designed using current PBD guidelines (PBD-compliant) to evaluate whether the current PBD criteria is sufficient for resisting aftershock effects. Additional PSDMs are generated for the columns with inadequate transverse reinforcement (PBD-deficient) to assess aftershock vulnerability of older bridges. The developed fragility curves indicate an increased fragility of all bridge piers for all damage levels. The findings indicate that adequate aftershock performance is achieved for bridge piers designed to current (2019) CHBDC extensive damage level criteria. Furthermore, it is suggested that minimal damage performance criteria need to be developed for aftershock effects, and the repairable damage level be reintroduced for major route bridges.