Initial errors and model errors are the source of prediction errors. In this study, the authors compute the conditional nonlinear optimal perturbation (CNOP)-type initial errors and nonlinear forcing singular vector (NFSV)-type tendency errors of the Zebiak-Cane model with respect to El Ni?o events and analyze their combined effect on the prediction errors for El Ni?o events. The CNOP-type initial error (NFSV-type tendency error) represents the initial errors (model errors) that have the largest effect on prediction uncertainties for El Ni?o events under the perfect model (perfect initial conditions) scenario. However, when the CNOP-type initial errors and the NFSV-type tendency errors are simultaneously considered in the model, the prediction errors caused by them are not amplified as the authors expected. Specifically, the prediction errors caused by the combined mode of CNOP-type initial errors and NFSV-type tendency errors are a little larger than those caused by the NFSV-type tendency errors. This fact emphasizes a need to investigate the optimal combined mode of initial errors and tendency errors that cause the largest prediction error for El Ni?o events.