AbstractClaims, disputes, and litigations are major legal issues in construction projects, which often result in cost overruns, delays, and adverse working relationships among the contracting parties. Recent advances in natural language processing (NLP) techniques offer great potentials that can process voluminous unstructured data from legal documents to draw insightful information about the root causes of issues and prevention strategies. Several efforts have been undertaken in the last decades that used NLP to tackle a wide range of problems related to legal issues in construction such as the quality review of contracts and the identification of common patterns in legal cases. The research line on NLP-based techniques for analyzing legal texts of construction projects has progressed well recently; it, however, is still in the early stage. This paper aims to perform a critical review of recently published articles to analyze the achievements and limitations of the state of the art on NLP-based approaches to address common legal issues associated with legal documents arising across different project stages. The study also provides a roadmap for future research to expand the adoption of NLP for the processing of legal texts in construction.