We proposed the leave-two-out method (i.e. one particular implementation of the nested cross-validation) to determine the optimal statistical crop model (using the validation dataset) and estimate its true generalization ability (using the testing dataset). This approach is applied to two examples (robusta coffee in Cu M'gar and grain maize in France). The results suggested that the simple models are more suitable in crop modelling where a limited number of samples is available.