BACKGROUND: Respiratory syncytial virus (RSV) is a leading cause of respiratory disease in young children. A number of mathematical models have been used to assess the cost-effectiveness of RSV prevention strategies, but these have not been designed for ease of use by multidisciplinary teams working in low-income and middle-income countries (LMICs). METHODS: We describe the UNIVAC decision-support model (a proportionate outcomes static cohort model) and its approach to exploring the potential cost-effectiveness of two RSV prevention strategies: a single-dose maternal vaccine and a single-dose long-lasting monoclonal antibody (mAb) for infants. We identified model input parameters for 133 LMICs using evidence from the literature and selected national datasets. We calculated the potential cost-effectiveness of each RSV prevention strategy (compared to nothing and to each other) over the lifetimes of all children born in the year 2025 and compared our results to a separate model published by PATH. We ran sensitivity and scenario analyses to identify the inputs with the largest influence on the cost-effectiveness results. RESULTS: Our illustrative results assuming base case input assumptions for maternal vaccination ($3.50 per dose, 69% efficacy, 6 months protection) and infant mAb ($3.50 per dose, 77% efficacy, 5 months protection) showed that both interventions were cost-saving compared to status quo in around one-third of 133 LMICs, and had a cost per DALY averted below 0.5 times the national GDP per capita in the remaining LMICs. UNIVAC generated similar results to a separate model published by PATH. Cost-effectiveness results were most sensitive to changes in the price, efficacy and duration of protection of each strategy, and the rate (and cost) of RSV hospital admissions. CONCLUSIONS: Forthcoming RSV interventions (maternal vaccines and infant mAbs) are worth serious consideration in LMICs, but there is a good deal of uncertainty around several influential inputs, including intervention price, efficacy, and duration of protection. The UNIVAC decision-support model provides a framework for country teams to build consensus on data inputs, explore scenarios, and strengthen the local ownership and policy-relevance of results.