The primary objective in corn production is to produce maximum yield, but many factors can interact to reduce yields. Crop models can be used as management tools to maximize returns to the producer and help manage resources. However, crop models need to accurately predict yield and yield components to be accepted on a large scale. The objective of this study was to evaluate and compare the simulation of kernel number and yield in the CERES-Maize crop model using four equations for kernel number calculation. Data sets from various plant populations, planting dates, and hybrid maturities under irrigated and dryland conditions from Kansas were used for evaluation of the four kernel number calculation methods incorporated into CERES-Maize version 3.51. None of the four equations adequately simulated kernel number across plant populations, locations, and hybrids for irrigated or dryland conditions. Simulated kernel numbers were generally high at low kernel numbers and low at high kernel numbers. However, under irrigated conditions kernel number was better simulated for late hybrids than for early hybrids. None of the equations accounted for a significant portion of the variability in kernel number under dryland conditions. Simulated yield was high at low yield levels and low at high yield levels under irrigated conditions with all four equations. The inability of these equations to accurately simulate kernel number may have affected the accuracy of yield simulations. Therefore, factors such as average plant growth rates and intercepted radiation during critical periods around silking need to be examined more closely if kernel number and yield are to be accurately simulated.