In the absence of epidemiological, microbiological or outbreak data, systematic identification of the hazards and food products posing the higher risk to the consumers is challenging. It is usually in Low- and Middle-Income Countries (LMICs), where the burden of foodborne disease is highest that data tend to be particularly scarce. In this study, we propose qualitative risk-ranking methods for pathogens and food products that can be used in settings where scarcity of data on the frequency/concentration of pathogens in foodstuff is a barrier towards the use of classical risk assessment frameworks. The approach integrates the existing knowledge on foodborne pathogens, manufacturing processes and intrinsic/extrinsic properties of food products with key context-specific information regarding the supply chain(s), characteristics of the Food Business Operators (FBOs) and cultural habits to identify: (i) the pathogens that should be considered as a “High” food safety priority and (ii) the food products posing the higher risk of consumer exposure to microbiological hazards via the oral (ingestion) route. When applied to the dairy sector of Andhra Pradesh (India) as a case study, Shiga toxin-producing E. coli, Salmonella spp., S. aureus and L. monocytogenes were identified as a “High” food safety priority across all FBOs. C. sakazakii was identified as a “High” priority for the FBOs producing infant formula/milk powder whilst Shigella spp., and Cryptosporidium spp. a “High” priority when considering the FBOs operating in the unregulated sector. Given the diversity of dairy products considered in the assessment, cluster analysis was used to identify products that shared similar intrinsic/extrinsic features known to drive the microbiological risk. The risk ranking was then done integrating the results of the cluster analysis with context-specific information. Products manufactured/retailed by FBOs in the informal market were considered as posing a “High” risk for the consumers due to a widespread lack of compliance to sanitary regulations. For dairy products produced by FBOs operating in the middle and formal end of the formal-informal spectrum, the risk of consumers exposure to microbiological hazards ranged from “Moderate” to “Extremely low” depending on the FBO and the intrinsic/extrinsic properties of the products. While providing risk estimates of lower precision if compared to data-driven risk assessments, the proposed method maximises the value of the information that can be easily gathered in LMICs and provide informative outputs to support food safety decision-making in contexts where resources to be allocated for prevention of foodborne diseases are limited and the food system is complex.