With the climate crisis progressing, the demand for scientific evidence from Climate Risk and Vulnerability Assessments (CRVA) has increased significantly in the last decade. Impact Chain-based CRVA (IC-based CRVA), an assessment method detailed in the Vulnerability Sourcebook, is capable of producing scientifically robust and actionable results that regularly find their way into decision-making. The method focuses on disentangling climate risk drivers within complex socio-ecological systems in a participatory and data-driven manner. Past applications have shown both methodological strengths and weaknesses and have revealed possible new application fields in research and policy. This article discusses a) advancements of the methodological toolset used in IC-based CRVA, and b) new application fields. The methodological advancements suggested herein are based on insights gained through eleven case studies set across Europe in different sectors during the course of the research project UNCHAIN. We propose advancements in the stakeholder engagement process, including methods to capture dynamics between risk factors, resolve contradictory worldviews of participants, uncover hidden vulnerabilities, use scenario-planning techniques, and retain consistency between Impact Chains across policy scales. Advances in the data-driven, operational modules include the integration of uncertainties via Probability Density Functions, using Reverse Geometric Aggregation to account for extreme risk factors and integrating macro-economic models to reflect possible future socio-economic exposure. Furthermore, we examine IC-based CRVAs’ applicability to address transboundary climate risks and climate risks for industry stakeholders. We conclude that the modular structure of IC-based CRVA permitted integrating various methodological advancements from different scientific disciplines and that, even after a decade in use, the method still offers possibilities to further its potential to understand and assess complex climate risks.