Evaluating the consequences to fish from blade-strike on marine hydrokinetic (MHK) turbine blades is important for incorporating environmental objectives into the integral optimization of machine performance. For instance, experience with conventional hydroelectric turbines has shown that innovative shaping of the blade and other machine components can improve hydraulic performance while reducing negative impacts to fish and other aquatic life. In this work, we used unsteady computational fluid dynamics (CFD) simulations of turbine flow and discrete element modeling (DEM) of particle motion to estimate the frequency and severity of collisions between a horizontal axis MHK tidal energy device and drifting aquatic organisms or debris. Two metrics are determined with the method: the strike frequency and the survival rate estimate. To illustrate the procedure step-by-step, an example case of a simple runner model was run and compared against a probabilistic model widely used for strike frequency evaluation. The results for the example case showed a strong correlation between the two approaches. In the application case of the actual MHK turbine flow, turbulent flow was modeled using detached eddy simulation (DES) in conjunction with a full moving rotor. The CFD-simulated power and thrust were satisfactorily comparable to experimental results conducted in a water tunnel on a reduced-scale (1:8.7) version of the turbine design. A cloud of DEM particles was injected into the domain to simulate fish or debris entrained into the turbine flow. Because various studies have pointed out the importance of fish volitional behavior, an assumed avoidance rate of 90% was applied to the particle sample. The strike frequency was the ratio of the count of colliding particles to the crossing sample size. The fish length and approaching velocity were test conditions in the simulations of the MHK turbine. Comparisons showed that DEM-based frequencies tend to be greater than previous results from Lagrangian particles and probabilistic models, mostly because the DEM scheme accounts for both the geometric aspects of the passage event —which only the probabilistic method does— as well as the fluid-particle interactions —which only the Lagrangian particle method does. With the full particle sample (0% avoidance), the DEM-based survival rates were generally high (above 90% in all studied cases), and comparable to previously reported laboratory results for small fish but not for mid-size fish mainly because of the considerable differences in rotor design between the CFD and laboratory models. With an assumed avoidance rate of 90%, the survival rates increased to nearly 99% across all scenarios. These results point to the need for further research and development of field monitoring methods for operating turbines to better understand the potential interaction between fish and MHK devices. The modeling framework can be used for applications that aim at evaluating the biological performance of MHK turbine units during the design phase and to provide information to regulatory agencies needed for the environmental permitting process.