Wildlife management and conservation is becoming ever more complex. Concomitantly, managers are in need of simple quantitative approaches and tools that could help them to make better management decisions. We present an approach that consists of generating a single simulated data set of expected data using a reference model, to which various capture–recapture models can be fitted. Using the general-purpose capture–recapture software M-SURGE, we apply this approach to bias, precision, and power calculations. After a quick statistical background refresher, we illustrate this approach with 3 simple examples: 1) the bias induced on survival by capture heterogeneity, 2) the precision of an estimate in the context of a reward-band study, and 3) the power of a test for detecting compensatory mortality. We believe this numerical approach based on expected values can potentially be applied to complex cases, thus making it possible to deal with real situations. We advocate that bias, precision, and power calculations be more routinely performed at the design stage of management or conservation studies. We believe the method we present can become a valuable tool to facilitate wildlife management and conservation.