Digital twins (DT) present a paradigm shift in how engineers construct and interact with a digital model. Due to material variance complexity in making reliable forward predictions, the implementation of DT in geotechnical engineering lags the other fields. To address these challenges, new standards, guidelines, and methodologies need to be developed specific to geotechnical engineering. Recent advancements in the application of multi-optimization (MOO) algorithms have demonstrated the possibility of achieving optimal design solutions having considered various design performance and economic objectives in geotechnical design. This contribution explores the use of MOO in the context of DT in geotechnical engineering. The use of MOO in a DT model can deliver an optimal set of model parameters tailored to the geotechnical design. The integration of a multi-objective design approach in a DT model framework simplifies the decision-making process at the early stages of a project where any design change is still highly effective and cost-efficient to implement.