In regions with low surface visibility, archaeologists often turn to systematic subsurface testing for purposes of site location. While numerous factors impact both the effectiveness and efficiency of these prospection efforts, “cookie-cutter” survey strategies are often employed without a thorough examination of their costs and benefits, and the results of such surveys are subject to erroneous interpretation when factors like effectiveness and limits of detection are not taken into account. In this presentation, we examine how a simulation-based approach that incorporates prior data can probabilistically determine the effectiveness and efficiency of different survey strategies. Beyond permitting the design of survey strategies that maximize the possibility of site detection and husband precious resources (time, money), this method also permits the generation of post hoc correction factors that make possible the critical evaluation and direct comparison of previous survey results.