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Floods are one of the most devastating natural hazards, and modelling them is extremely difficult. Flood prediction model advancement study led to factors such as loss of human and animal life, property damage, and risk mitigation. The focus of this bibliometric survey is to recognise the few studies which have upheld on the factors affecting the floods. The analysis is done based on 254 documents such as articles, conference papers, article reviews and some reviews and notes. India contributes to the maximum number of documents followed by China and the United States of America. This bibliometric survey is conducted using Scopus. The survey includes analysis by the type of country or territory the documents are written in, authors contributing to the area of research, and statistical analysis based on citations, subject areas, and source types. This bibliometric survey revealed that the maximum numbers of publications on flood prediction using machine learning are from articles, etc, affiliated with Duy Tan University in the year 2020. Most of the research (i.e., 22.6%) is carried out by the Environmental Sciences department. Citation's graph shows that highest numbers of citations are in the year 2020.