User-friendly models (UFMs) allow local decision makers to explore relationships and apply results from more detailed models of such outcomes as cost-effectiveness. When developing UFMs, modelers must decide which simplifications may be appropriate, enabling the UFM to retain accuracy while reducing complexity. We use the example of cost-effectiveness analysis (CEA) for novel shortened anti-tuberculosis treatment regimens across four settings to demonstrate how UFMs can allow decision makers to adapt published results to their local context. We simplified a complex model to produce a UFM that provides similar results, the ability to modify key parameter values, and receive customized results in seconds.