Sustainable management of terrestrial hunting requires managers to set quotas restricting offtake. This often takes place in the absence of reliable information on the population size, and as a consequence, quotas are set in an arbitrary fashion, leading to population decline and revenue loss. In this investigation, we show how an indirect measure of abundance can be used to set quotas in a sustainable manner, even in the absence of information on population size. Focusing on lion hunting in Africa, we developed a simple algorithm to convert changes in the number of safari days required to kill a lion into a quota for the following year. This was tested against a simulation model of population dynamics, accounting for uncertainties in demography, observation, and implementation. Results showed it to reliably set sustainable quotas despite these uncertainties, providing a robust foundation for the conservation of hunted species. management strategy evaluation | control rule | operating model | matrix model S ustainable management of exploited biological resources is often hampered by insufficient information on either population size or the dynamic response to harvesting. In terrestrial trophy hunting systems, even though target species biology may be well studied, the population size itself is often poorly estimated. Abundance data are limited in time and space, making informed management decisions problematic. In response to economic pressure, quotas are often set too high, leading to population decline and a loss of long-term economic revenue (1). The trophy hunting of animals for sport can have significant conservation benefits (2-4), but there is an urgent need for methods that will allow sustainable management.Deriving robust means to set sustainable limits to exploitation is now a well-developed science, increasingly applied to marine fisheries (5), and referred to as management strategy evaluation (MSE) (6). Within this framework, process-based simulations are used to test the performance of a quota setting algorithm (the control rule) against management targets. Including uncertainty in the projections allows development of a control rule that is robust to incomplete knowledge of resource status or its response to harvesting, implicitly conforming to the precautionary principle of resource management (7).We derive a control rule that is able to set sustainable quotas in the absence of any information on population size and use MSE to evaluate its performance. The context is provided by lion (Panthera leo) hunting in sub-Saharan Africa, which exemplifies the problems associated with sustainable management of terrestrial hunting systems. Lion quotas are generally set by government and allocated to private hunt operators that then sell hunting safaris to individual clients. A successful hunt yields a fixed trophy fee, which is usually accrued by the local statutory authority. The daily fees (which are accrued regardless of the success of a hunt) conferred to hunt operators by paying clients can be an import...