Reliability modelling has become increasingly important in engineering, software systems, infrastructure management, and artificial intelligence applications due to the growing complexity and interconnectedness of modern systems. Despite the rapid expansion of reliability-related research, a comprehensive bibliometric understanding of the field’s intellectual structure, thematic evolution, and global collaboration patterns remains limited. This study presents a detailed bibliometric analysis of reliability model research from 1989 to 2024, using data from 2,037 scholarly records indexed in the Web of Science database. It reveals a steady annual growth rate of 10.37 percent, showing the increasing importance of reliability research across academic and industrial sectors. With the help of tools like Bibliometrix in R and VOSviewer, the study maps collaboration networks, key research themes, and emerging trends. The focus of research has expanded from traditional topics such as system failures and fault tolerance to modern concerns like software reliability, predictive modelling, and the use of artificial intelligence in optimization. International collaboration, particularly among China, the United States, India, and Australia, has played a vital role in shaping a more global and diverse research landscape. This study also connects reliability research with the United Nations Sustainable Development Goals, highlighting contributions to clean energy, smart systems, and resilient infrastructure. This work will benefit researchers, engineers, and policymakers by offering a clear direction for future studies that can improve system safety, performance, and societal resilience.