The Electronic Journal of Probability, published by the Institute of Mathematical Statistics (IMS), is a premier open access journal dedicated to the dissemination of innovative research in the field of probability theory. Since its inception in 1996, it has emerged as a leading platform for scholars, researchers, and practitioners to share their findings and explore new methodologies. With an impressive track record and a commitment to free accessibility, the journal covers a broad scope of topics within statistics and probability, validated by its prestigious rankings in the Q1 quartile for both Statistics and Probability. Its influence is further evidenced by its consistent presence in the academic community and its contribution to advancing understanding in probability and uncertainty. The journal's ongoing dedication to promoting open scholarship ensures that high-quality research remains accessible to all, fostering collaboration and innovation among professionals and students alike.

COMBINATORICS PROBABILITY & COMPUTING is a premier journal published by Cambridge University Press, focusing on the cutting-edge fields of combinatorics, probability, and their computational aspects. Established in 1992 and set to continue its impactful discourse through 2024, this journal holds a distinguished reputation, reflected in its Q1 ranking in applied mathematics, computational theory, and statistics, showcasing its pivotal role in advancing research in these areas. With an ISSN of 0963-5483 and an E-ISSN of 1469-2163, the journal welcomes high-quality papers that contribute to the theoretical foundations and practical applications of the disciplines. While it is not available as open access, its accessibility through institutional subscriptions ensures wide readership within academia. The journal is a vital resource for researchers, professionals, and students alike, providing a platform for innovative ideas and pioneering research that shapes the future of mathematics and computer science.

Applied Mathematics and Optimization, published by Springer, is a prestigious journal dedicated to the rigorous exploration of applied mathematics, optimization techniques, and their multifaceted applications. Since its inception in 1974, the journal has maintained a robust reputation within the academic community, achieving a commendable Q1 ranking in both Applied Mathematics and Control and Optimization categories as of 2023. With an impact factor that underscores its influence in the field, the journal provides a platform for researchers and practitioners to disseminate innovative methodologies and significant advancements. While it does not offer Open Access, the journal’s esteemed peer-reviewed articles serve as invaluable resources for the advancement of theoretical knowledge and practical applications. Researchers, professionals, and students alike will find Applied Mathematics and Optimization an essential source for staying at the forefront of mathematical sciences, particularly in optimizing real-world systems and processes.

PROBABILITY THEORY AND RELATED FIELDS is a premier journal published by SPRINGER HEIDELBERG, dedicated to advancing the field of probability and its applications. With an ISSN of 0178-8051 and an E-ISSN of 1432-2064, this journal has established itself as a leading platform for innovative research, featuring significant contributions to the theories and methodologies in probability, statistics, and uncertainty analysis. Its impressive ranking in the 2023 category quartiles places it in the Q1 tier within Analysis, Statistics and Probability, highlighting its importance in the academic community. The journal is widely recognized for its rigorous peer-review process, ensuring high-quality publications that cater to researchers, professionals, and students alike. Located in Germany at TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, it continues to shape the future of statistical sciences from 1986 until 2024 and beyond. Researchers in the field are encouraged to contribute their findings, ensuring the journal remains at the forefront of innovative statistical research.

Markov Processes and Related Fields, published by POLYMAT, is a pivotal journal in the field of applied mathematics and statistics, aimed at researchers, practitioners, and students who seek to deepen their understanding of complex stochastic processes and their applications. With an ISSN of 1024-2953 and a convergence of scholarly work from 2012 to 2023, this journal not only contributes to the discourse around Markov processes but also positions itself within the competitive landscape of academic publishing, as evidenced by its Q4 ranking in both Applied Mathematics and Statistics and Probability for 2023. While the journal is not open access, it provides critical insights and developments that are essential for driving forward research in these fields. The journal's contributions enhance knowledge transfer among academia and industry, fostering innovation and application in various sectors. As researchers and students engage with its content, they will find a wealth of information that challenges conventional thinking and encourages novel approaches to statistical modeling and analysis.

The Journal of Theoretical Probability is a prominent academic journal dedicated to the dissemination of cutting-edge research in the fields of probability theory and its applications. Published by Springer/Plenum Publishers, this journal has established itself as a vital resource for researchers and professionals interested in theoretical advancements and practical implementations within the realm of mathematics, particularly in the categories of Statistics and Probability. With an impressive converged publication trajectory from 1988 to 2024, the journal holds a commendable Q2 quartile ranking across various disciplines including Mathematics and Statistics and Probability as indicated in the 2023 metrics. Although not Open Access, the journal continues to attract high-quality submissions that contribute significantly to the field, making it an essential platform for advancing theoretical understanding and fostering academic dialogue. Whether you are a seasoned researcher or a graduate student, the Journal of Theoretical Probability offers valuable insights and rigorous scholarship that can enhance your academic pursuits.

ADVANCES IN APPLIED PROBABILITY is a prestigious academic journal published by Cambridge University Press, focusing on the critical intersection of applied mathematics and probability theory. With an ISSN of 0001-8678 and an E-ISSN of 1475-6064, this journal emphasizes the development and application of probabilistic models in various sectors, enhancing the rigor and reliability of statistical methodologies. Established in 1969, the journal has evolved with converged years designated up to 2024, maintaining a steady release of cutting-edge research. As a Q2-ranked journal in both Applied Mathematics and Statistics and Probability categories as of 2023, it ranks favorably within the Scopus database, demonstrating its growth in influence and relevance within the academic community, with ranks of 141/278 and 353/635 in its respective fields. Although it does not offer open access, the journal remains a vital resource for researchers, professionals, and students seeking to advance their knowledge and understanding of probability applications across diverse disciplines.

Communications in Mathematics and Statistics, published by Springer Heidelberg, is a prominent journal dedicated to advancing research in the fields of applied mathematics, computational mathematics, and statistics. With an ISSN of 2194-6701 and an E-ISSN of 2194-671X, the journal has established itself as a vital platform for interdisciplinary scholarly communication since its inception in 2013. The journal falls within the third quartile in various rankings including applied mathematics, computational mathematics, and statistics and probability, indicating its solid position in the global research landscape. With a focus on innovative methodologies and practical applications, Communications in Mathematics and Statistics aims to bridge the gap between theoretical research and practical implementation. Researchers, professionals, and students alike will find valuable insights and cutting-edge studies that contribute to the evolution of mathematical sciences. The journal is based in Germany, with a commitment to fostering international collaboration and accessibility in mathematical research.

STATISTICS & PROBABILITY LETTERS is a distinguished journal published by ELSEVIER, dedicated to advancing the field of statistics and probability. With an ISSN of 0167-7152 and an E-ISSN of 1879-2103, this journal is an essential platform for research, featuring cutting-edge studies and significant findings in the realms of statistical theory and applied probability. The journal operates under a notable Q3 ranking in both the categories of Statistics and Probability, and Statistics, Probability and Uncertainty for 2023, underscoring its relevance in these fields. Researchers, professionals, and students alike benefit from its rigorous peer-review process and its commitment to published integrity, fostering innovative insights from 1982 through its anticipated convergence in 2025. While it does not offer open access, the journal’s widely recognized impact within the academic community makes it a valuable resource for anyone seeking to deepen their understanding of statistical methodologies and probabilistic models.

STOCHASTIC PROCESSES AND THEIR APPLICATIONS, published by Elsevier, is a leading journal in the realms of Applied Mathematics, Modeling and Simulation, and Statistics and Probability. Established in 1973 and continually evolving with the latest research trends, this journal has secured its place in the Q1 category across multiple disciplines, reflecting its influence and prestige in the academic community. With a Scopus Rank of #90 in Statistics and Probability and notable rankings in Applied Mathematics and Modeling and Simulation, it serves as a crucial platform for disseminating cutting-edge research findings and applications of stochastic processes. Although it operates under a traditional access model, its comprehensive scope encourages submissions from a diverse range of topics that push the boundaries of knowledge in probability theory and its practical applications. Researchers, professionals, and students are invited to contribute original research, reviews, and case studies that can propel the field into new territories, further solidifying the journal's role as an essential resource for advancing understanding in stochastic processes.