The book “Theory of Pattern Recognition in Economic Research”, created by the team of authors, is a fascinating and in-depth study that opens up new horizons in the field of economic analysis and forecasting. This work will become an indispensable tool for students, graduate students, teachers and practicing economists seeking to understand how modern methods of pattern recognition can be applied to solve complex economic problems. The focus of the book is pattern recognition theory, an area that is actively developing thanks to advances in machine learning and artificial intelligence. The authors examine in detail how these technologies can be used to analyze large amounts of data, identify hidden patterns and trends, and make predictions that can significantly affect economic decision-making. In a rapidly changing world, where information is becoming a key resource, the ability to recognize and interpret economic “images” is becoming a necessary skill. The book is addressed to a wide audience: from students studying economics and statistics to experienced professionals working in the field of data analysis and economic forecasting. It will be of interest to those who want to expand their knowledge of modern methods of data analysis and their application in economics. Readers who are passionate about new technologies and their impact on economic processes will find many useful ideas and practical recommendations in this book. The topics raised in the book cover a wide range of issues, from the foundations of pattern recognition theory to specific examples of its application in economic research. The authors discuss how machine learning algorithms can help in identifying patterns in consumer behavior, analyzing financial markets and assessing economic risks. The book also touches on the ethical aspects of the use of technology in economics, making it particularly relevant in light of current discussions about the role of artificial intelligence in society. The style of the authors is distinguished by scientific rigor and accessibility, which makes it easy to assimilate complex concepts. They use many examples and cases, which makes the material more clear and understandable. The book is not only informative, but also inspires further research in the field of economics and technology. In addition to the Theory of Pattern Recognition in Economic Research, readers may be interested in works such as Data Economics and Machine Learning for Economists, which also explore the intersection of economics and technology. These books will help deepen our understanding of current trends and methods used in economic analysis. Thus, “The Theory of Pattern Recognition in Economic Research” is not just a textbook, but a real find for anyone interested in how modern technology can change the approach to economic research. This book will be a faithful companion on the way to understanding complex economic phenomena and will help readers learn new tools that open up endless horizons of opportunities for them.