The bioeconomy has the potential to contribute significantly to sustainable development and a just transition. To ensure the sustainable production of bio-based products, it is essential to understand their potential environmental, economic, and social impact. However, the social dimension receives far less attention in sustainability literature and assessments than the environmental and economic dimensions. Especially in the Global South, where a large part of the world's biomass is produced, vulnerable communities are at higher risk of being negatively affected by the bioeconomy. These risks include food insecurity, monoculture expansion, and unequal wealth distribution. Therefore, it is crucial to understand new bio-based value chains' (potential) social impacts better. This paper contributes to this debate by developing a prospective Social Life Cycle Assessment (SLCA) for a bush-based value chain in Namibia. We assessed the existing charcoal value chain and identified potential social risks, impacts, and opportunities of a prospective value chain to produce marine biofuels from encroacher bush. We use this case study to reflect on the SLCA methodology and compare the SLCA results with our qualitative fieldwork based on interviews and a multi-stakeholder workshop. We found that the current methods for SLCA do not adequately capture salient aspects of the local context. SLCA is a good method to quantify some social impacts and to identify social risks in the value chain, such as labor conditions and existing policies. However, the methodology of SLCA currently misses a more nuanced understanding of the context and potential social issues, like issues related to gender and ethnicity, and the adherence to existing policies. We propose adding more context-specific indicators to the risk assessment. In addition, stakeholder engagement is crucial for identifying and assessing relevant social impact categories, and we advocate for incorporating local stakeholders' subjective assessments. This approach allows for the inclusion of softer social impact categories, such as gender and ethnicity-related social norms, which are not easily captured by general indicators.