This chapter reviews the general procedures and methodologies used for validating growth and yield models. More specifically, it addresses: (i) the optimism principle and model validation; (ii) model validation procedures, problems and potential areas of needed research; (iii) data considerations and data-splitting schemes in model validation; and (iv) operational thresholds for accepting or rejecting a model. The roles of visual or graphical validation, dynamic validation, as well as statistical and biological validations are discussed in more detail. The emphasis in this chapter is placed on the understanding of the validation process rather than the validation of a specific model. The limitations and the pitfalls of model validation procedures, as well as some of the frequent misuses of these procedures are discussed. Several technical and practical recommendations concerning the validation of growth and yield model are made.