Science strives towards a credible and comprehensive understanding of the world around us. Across disciplines within the social and behavioural sciences (and beyond), limitations in the implementation of the scientific approach have been identified in recent studies, showing low replicability of many results. This is an issue for knowledge accumulation, theory-building, and evidence-based decision and policy making. Researchers have proposed several solutions to address these issues, focusing mainly on improving statistical methods, data quality, and transparency. However, relatively little attention has been paid to another key aspect that affects replicability: language. Across fields, language plays a central role in all steps of the research cycle and is a critical communication tool among researchers. Neglecting its role may reduce replicability and limit our understanding of theoretically interesting differences and similarities across languages. After identifying these challenges, we provide some recommendations and an outlook on how replicability challenges related to language may be addressed.