Bio-indexing of hydro turbines is an important means to optimize passage conditions for fish by identifying operations for existing and new design turbines that minimize the probability of injury. Cost-effective implementation of bio-indexing requires the use of tools such as numerical and physical turbine models to generate hypotheses for turbine operations that can be tested at prototype scales using live fish. Numerical deterministic and stochastic blade-strike models were developed for a 1:25-scale physical turbine model built by the U.S. Army Corps of Engineers for the original design turbine at McNary Dam and for prototype-scale original design and replacement minimum gap runner (MGR) turbines at Bonneville Dam’s first powerhouse. Blade-strike probabilities predicted by both models were comparable with those observed in both prototype-scale live fish survival studies and a physical turbine model using neutrally buoyant beads. Predictions from the stochastic model were closer to experimental data than predictions from the deterministic model because the stochastic model considered the aspects of fish approaching to the leading edges of turbine runner blades. Therefore, the stochastic model should be the preferred method for the prediction of blade strike and injury probability for juvenile salmon and steelhead using numerical blade-strike models for evaluating the biological performance of Kaplan hydro turbines.