We demonstrate the utility of models as aids in the design and development of experiments aimed at measuring the effects of proposed vector population control strategies. We describe the exploration of a stochastic, age-structured model that simulates field cage experiments that test the ability of a female-killing strain of the mosquito Aedes aegypti (L.) to suppress a wild-type population. Model output predicts that choices of release ratio and population size can impact mean extinction time and variability in extinction time among experiments. We find that unless fitness costs are >80% they will not be detectable in experiments with high release ratios. At lower release ratios, the predicted length of the experiment increases significantly for fitness costs >20%. Experiments with small populations may more accurately reflect field conditions, but extinction can occur even in the absence of a functional female-killing construct because of stochastic effects. We illustrate how the model can be used to explore experimental designs that aim to study the impact of density dependence and immigration; predictions indicate that cage population eradication may not always be obtainable in an operationally realistic time frame. We propose a method to predict the extinction time of a cage population based on the rate of population reduction with the goal of shortening the duration of the experiment. We discuss the model as a tool for exploring and assessing the utility of a wider range of scenarios than would be feasible to test experimentally because of financial and temporal restraints.