Journal of Mathematical and Analytical Data Science (J. Math. Anal. Data Sci.) is a peer-reviewed, open-access journal dedicated to the advancement of mathematics, analytical methods, and data science as fundamental disciplines for scientific discovery, technological innovation, and evidence-based decision making. The journal provides a scholarly platform for publishing high-quality original research and review articles that integrate mathematical theory, statistical analysis, computational techniques, and data-driven methodologies across diverse scientific and applied domains.

JMADS aims to bridge the gap between theoretical mathematics and practical data analytics, encouraging interdisciplinary research that combines mathematical modeling, statistical inference, machine learning, optimization, and analytical data processing. The journal welcomes contributions that develop new mathematical frameworks, propose innovative analytical methods, or apply advanced data science techniques to solve complex problems in science, engineering, economics, education, health, and social systems.

All manuscripts submitted to JMADS undergo a rigorous double-blind peer-review process conducted by independent experts to ensure originality, methodological soundness, clarity of presentation, and academic relevance. The journal upholds the highest standards of publication ethics, transparency, and research integrity, in accordance with international best practices.

JMADS publishes articles that emphasize theoretical contributions, methodological advancements, and applied analytical studies, including but not limited to mathematical modeling, statistical learning, data mining, computational mathematics, and analytical decision-support systems. By fostering collaboration between mathematicians, data scientists, statisticians, and interdisciplinary researchers, JMADS seeks to contribute significantly to the global development of mathematical and analytical data science research.