When selecting algorithms for real-time weapons effects, performance and fidelity requirements are the main drivers in model selection. In many cases, look-up tables are the method of choice for real-time applications. Look-up tables have had wide-spread use in trade studies, planning tools, training simulations and other applications over a long period and have proven to be both extremely valuable for real-time casualty assessment and at times misunderstood in what capabilities they provide. Look-up tables facilitate fast retrieval of vulnerability data, with measurable tradeoffs between memory requirements, computation requirements and fidelity. As processing power has increased, higher fidelity algorithms of casualty assessment have gained wider use, suggesting that look-up tables may eventually become obsolete. This paper describes the casualty assessment modeling spectrum from low fidelity to high fidelity, including look-up tables, curve fits, physics-based models and finite element codes. Each type of model is examined, along with the advantages and disadvantages of each. Guidelines for how to determine what model type to select and what factors should be considered when selecting a model are discussed. Principles outlined in this paper are being used to support model selection for the OneTESS program, the Army's next generation tactical engagement simulation system.