This study investigates the dynamic assessment of hydro turbines for effective power utilization in Kainji and Jebba dams. Hydro power plant mainly consists of three sections, governor (controller), hydro servo system and hydro turbine. The hydro turbine governor is usually coupled to a synchronous generator to drive the shaft so that the mechanical energy of turbine is converted to electrical energy. Accurate modeling of hydraulic turbine and its governor system is essential to depict and analyze the dynamic system response. In this work, both hydraulic turbine and turbine governor system were modeled. The hydro turbine model is designed using penstock and turbine characteristic equations. The simulation model is developed using MATLAB/SIMULINK. The dynamic response of the governing system to the disturbances such as load variation on the generator parameter during fault was presented. The results graphically demonstrate the effect of load variation on generator parameters under a three phase to ground fault. The transient behavior of generator voltage, current and the rotor speed are also captured. Similarly, two hydropower dams along the River Niger (Kainji and Jebba dams) in Nigeria were analyzed for energy generation using multilayer perceptron artificial neural network. Total monthly historical data of Kainji and Jebba hydropower reservoirs’ variables and energy generated were collected for a period of forty-two years (1980-2021) and (1994-2021) for the network training. These data were divided into training, testing and holdout data set. The neural network analysis yielded a good forecast for Kainji and Jebba hydropower reservoirs with correlation coefficients of 0.89 and 0.77 respectively. These values of the correlation coefficient showed that the networks are reliable for modeling energy generation as a function of reservoir variables for future energy prediction. Accordingly, the study recommended that Advanced Real-Time Controllers should be developed so as to reduce system oscillations and improve overall system stability, Parameter Tuning Methods should be implemented with the use of advanced optimization techniques, such as sensitivity analyses and automated parameter tuning algorithms, Hydro Turbine and Governor Models should be implemented with the use of real-time simulation tools, allowing for the integration of these models with other power systems, such as wind or solar power systems, Optimization Algorithms should be developed with the consideration of uncertainty in system parameters, operating conditions and Advanced Control Systems should be developed with the goal of improving grid resiliency and reliability..