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In this study, we presented a four-level cross-domain strategy for fake newsdetection on pre-trained models. Cross-domain text classification is a task ofa model adopting a target domain by using the knowledge of the source domain.Explainability is crucial in understanding the behaviour of these complexmodels. A fine-tune BERT model is used to. perform cross-domain classificationwith several experiments using datasets from different domains. Explanatorymodels like Anchor, ELI5, LIME and SHAP are used to design a novel explainableapproach to cross-domain levels. The experimental analysis has given an idealpair of XAI models on different levels of cross-domain.

A New cross-domain strategy based XAI models for fake news detection