We present the results and findings of the BAREC Shared Task 2025 on Arabic Readability Assessment, organized as part of The Third Arabic Natural Language Processing Conference (ArabicNLP 2025). The BAREC 2025 shared task focuses on automatic readability assessment using BAREC Corpus, addressing fine-grained classification into 19 readability levels. The shared task includes two sub-tasks: sentence-level classification and document-level classification, and three tracks: (1) Strict Track, where only BAREC Corpus is allowed; (2) Constrained Track, restricted to the BAREC Corpus, SAMER Corpus, and SAMER Lexicon, and (3) Open Track, allowing any external resources. A total of 22 teams from 12 countries registered for the task. Among these, 17 teams submitted system description papers. The winning team achieved 87.5 QWK on the sentence-level task and 87.4 QWK on the document-level task.

We present BAREC Demo, a web-based system for fine-grained, sentence-level Arabic readability assessment. The demo is part of the Balanced Arabic Readability Evaluation Corpus (BAREC) project, which manually annotated 69,000 sentences (over one million words) from diverse genres and domains using a 19-level readability scale inspired by the Taha/Arabi21 framework, covering reading abilities from kindergarten to postgraduate levels. The project also developed models for automatic readability assessment.The demo provides two main functionalities for educators, content creators, language learners, and researchers: (1) a Search interface to explore the annotated dataset for text selection and resource development, and (2) an Analyze interface, which uses trained models to assign detailed readability labels to Arabic texts at the sentence level.The system and all of its resources are accessible at https://barec.camel-lab.com.