Objective: This study provides a comprehensive scientometric analysis of scientific outputs in the field of natural computing from 1980 to 2022.

Methods: Data were extracted from the Web of Science database over a forty-year period. After filtering and standardizing raw records, Python programming was used to analyze indicators such as number of publications, authors, countries, institutions, journals, and keywords. Historical trends, thematic orientations, and patterns of international collaboration were also examined through co-word analysis.

Findings: Results reveal significant growth in the field, with publications increasing from one in 1984 to 51 in 2008, and the number of active authors reaching 140 by 2021. The United States, Spain, and China emerged as the leading contributors, while institutions such as the University of Seville and the Romanian Academy played pivotal roles in enhancing research quality. Key journals—including Theoretical Computer Science and Natural Computing—served as primary outlets for specialized work. Thematic developments demonstrate a shift from a focus on computer science toward applications in green chemistry. Influential keywords identified include “natural computing,” “membrane computing,” and “P system.”

Conclusion: The study highlights natural computing as a rapidly expanding interdisciplinary and transdisciplinary field. Beyond its foundational role in optimization and bioinformatics, natural computing has extended applications in data mining and information systems security. These findings underscore the field’s growing importance in advancing science and technology and its potential to address emerging research challenges across multiple domains.