Bangladesh, characterized by its riverine landscape, predominantly comprises deltaic land formed by the convergence of three powerful river systems: the Padma (Ganges), the Jamuna (Brahmaputra), and the Meghna. This geographical setting, combined with high rainfall and trans-boundary flows in the major rivers, renders the nation susceptible to severe floods. The evolving patterns of flood intensity and magnitude over recent decades signify the significant influence of rainfall variability and climate change. Historical data underscores the impact of floods, with major inundations affecting over 35% of the country post-1974, peaking at 68% in 1998. The consequences are far-reaching, leading to the displacement of residents, erosion along riverbanks, extensive damage to property and infrastructure, and resulting in significant monetary losses. The cumulative financial toll wrought by the floods of 1988, 1998, and 2004 amounted to approximately $2.0, $2.8, and $2.0 billion USD, respectively. While floods remain an inevitable natural phenomenon, the focus shifts toward mitigating their damage rather than attempting outright prevention. An integrated flood management approach, blending structural and non-structural measures, emerges as the pragmatic solution. While conventional structural measures are costly, non-structural strategies offer a more sustainable alternative, circumventing adverse environmental, social, and ecological impacts. Among these, flood vulnerability assessment and vulnerability-based management plans stand out as effective non-structural measures, particularly in river basins. In a comprehensive study focusing on the Jamuna river basin, flood vulnerability was meticulously evaluated using a multi-faceted methodology. Leveraging the IPCC framework, factors encompassing exposure, sensitivity, and adaptive capacity were scrutinized. Techniques such as frequency ratio analysis, support vector machine learning, and GIS were employed to ascertain flood probability and vulnerability. Following the IPCC framework, a comprehensive set of 16 factors was identified, comprising 9 for exposure, 4 for sensitivity, and 3 for adaptive capacity to floods. To gauge flood probability for each factor, we employed the frequency ratio (FR) approach, utilizing support vector machine (SVM) with a radial basis function (RBF) kernel to optimize parameters. Subsequently, physical and social vulnerability maps were crafted using the weighted sum method (WSM) and SVM-trained exposure and sensitivity factors, respectively. Guided by the IPCC guideline, we integrated the physical and social vulnerability maps to assess potential flood vulnerability comprehensively. Finally, a refined flood vulnerability map was delineated by factoring in adaptive capacity, thus offering a holistic perspective on the region's vulnerability to flooding. The culmination of these efforts yielded detailed physical and social vulnerability maps, offering insights into areas of heightened susceptibility. Notably, approximately half of the basin exhibited high to very high flood vulnerability, warranting urgent intervention. These findings underscore the imperative for robust flood management strategies tailored to the region's specific needs. The study’s implications extend beyond academia, offering actionable insights for planners and policymakers. By minimizing exposure and sensitivity to flooding, the proposed strategies pave the way for disaster risk reduction and the safeguarding of livelihoods in river floodplains. In essence, this work serves as a blueprint for navigating the complex interplay between natural phenomena and human habitation, ensuring the resilience and sustainability of flood-prone regions like Bangladesh.