<p>Reliable waste estimates are fundamental for developing efficient waste management strategies by promoting resource efficiency and sustainable construction practices. Although various researchers have developed methods and tools globally to estimate waste, there is a dearth of focused research which integrates the past studies to understand the growing trend and evolution on the subject, which can help identify under-explored or neglected areas. This study uses a science mapping approach to analyze construction waste estimation methods literature. First, bibliometric search of the Scopus database (2000–2024) identified relevant articles. Then for the scientometric analysis, VOSviewer version (v1.6.20) was used to identify and analyze the publication trends, active countries, influential journals and authors and keywords that contributed the most in the waste estimation research globally. Results show that only 10 countries have published more than 2 articles in the past, with China leading the research. Concrete, construction stages, machine learning, prediction model and residential buildings are the top 5 emerging keywords. Information management, predictive modeling, classification and composition and material data modeling are the top emerging research themes deduced by an in-depth qualitative assessment. The results highlighted a rising interest in adoption of BIM and AI tools in waste estimation methods. This study overviews the latest research in construction waste estimation methods, serving researchers and industry professionals by identifying current gaps and future research directions and practical implications.</p>