The sustainability of bridge infrastructure is becoming increasingly important due to rising environmental, economic, and social demands. However, most current assessment models remain fragmented, often overlooking the social pillar, underutilizing risk integration across the lifecycle, and failing to fully leverage digital tools such as Building Information Modeling (BIM) and Life Cycle Sustainability Assessment (LCSA), resulting in incomplete sustainability evaluations. This study addresses these limitations by introducing a practical and adaptable model that integrates BIM, LCSA, and expert-driven risk prioritization. Five Hungarian bridge projects were modeled using Tekla Structures and analyzed in OpenLCA to quantify environmental, economic, and social performance. A custom Sustainability Level Change (SLC) algorithm was developed to compare baseline scenarios (equal weighting) with risk-informed alternatives, simulating the impact of targeted improvements. The results demonstrated that prioritizing high-risk sustainability indicators leads to measurable lifecycle gains, typically achieving SLC improvements between +2% and +6%. In critical cases, targeted enhancement scenarios, applying 5% and 10% improvements to top-ranked, high-risk indicators, pushed gains up to +12%. Even underperforming bridges exhibited performance enhancements when targeted actions were applied. The proposed framework is robust, standards-aligned, and methodologically adaptable to various bridge types and lifecycle phases through its data-driven architecture. It empowers infrastructure stakeholders to make more informed, risk-aware, and data-driven sustainability decisions, advancing best practices in bridge planning and evaluation. Compared to earlier tools that overlook risk dynamics and offer limited lifecycle coverage, this framework provides a more comprehensive, actionable, and multi-dimensional approach.