LCA is essential for achieving the European Green Deal's targets and supporting sustainable development. As LCA tools become more complex, multivariate statistics can offer valuable solutions. However, their potential benefits in LCA are yet to be fully explored. Therefore, this review evaluates scientific publications combining both, focusing on evaluating the fields of application and potential of multivariate statistics in LCAs. Key findings were the identified use cases, which can be categorised as "Grouping of Products/Systems", "Reduction of Parameters", "Evaluation of Parameters", and "Support for Decision Makers". Among these, the evaluation of parameters was the most commonly used category, with Principal Component Analysis (PCA) being the most frequently used statistical method. Although the publications showed high potential for gaining information, there is a lack of publications combining both topics. They were often used for high Technology Readiness Levels and often based on small datasets, although large data sets are desirable for gaining reliable and robust results. Therefore, future work will need to validate the data requirements and statistical methods recommended per use case.