Under the influence of economic globalization and the transformation of pillar industries, cities are facing phenomena such as slow economic growth and population outflow, which indicate urban shrinkage. However, the theoretical framework for this phenomenon remains incomplete, and measurement standards are inconsistent. Therefore, studying urban shrinkage is of significant importance. This paper analyzes the current status and causes of urban shrinkage in Liaoning Province, China, and proposes an accurate model for identifying shrinkage. It utilizes a two-step diagnostic method that incorporates both one-dimensional and multidimensional approaches to identify shrinking cities and applies systematic clustering methods to categorize urban population changes. By observing and analyzing the population and economic data of 30 cities over 12 years, this study assesses urban shrinkage from the perspectives of population change and multivariate indicators. It identifies five cities with significant shrinkage, categorized into mild, moderate, and severe levels. Based on multiple linear regression and grey relational analysis, the study examines the impact of socio-economic factors on population changes and offers corresponding development suggestions.