Effector proteins are of interest in the field of fungal plant pathology due to their ability to mediate disease infection in plants, particularly devastating fungal infections in economically important agricultural crops. The discovery of new fungal effector proteins is necessary to enable the screening of cultivars for disease resistance. However, fungal effector proteins lack sequence similarity and conserved sequence motifs, which poses a significant obstacle for sequence-based prediction. Experimental determination of the three-dimensional (3D) structure of effector proteins is slowly allowing the identification of structural motifs to predict new effector proteins in fungi. Currently, nine effector structural families have been identified, but many more structural folds are believed to exist beyond these families due to the diversity in pathogenicity of fungal effectors. We have applied both template and non-template based (ab initio) structural modelling to predict the 3D structures of experimentally verified fungal effector proteins whose structures have not yet been resolved. RaptorX threading provides higher accuracy over conventional sequence-based alignment in homology modelling. Accurate selection of templates during threading enabled the prediction of pathogenicity-related folds and domains that are potentially new to known effector structural families. Rosetta ab initio modelling was implemented for effector proteins below the scoring threshold resulted from threading. Interestingly, several ab initio models had strong matches with known protein folds that were not identified during threading. The best predicted models were assessed for relevant domain and fold information, and the quality of the models. We demonstrate that the combination of threading and ab initio modelling can be a successful strategy to expand the database of potential effector protein structural families. This could be applied for the prediction of the interactions of effector proteins with their plant receptors to improve our understanding of their mechanism of interaction with the host.