Over the years, a number of approaches have been proposed on the description of systems and software in terms of multiple views represented by models. This modelling branch, so-called multi-view software and system modelling, praises a differentiated and complex scientific body of knowledge. With this study, we aimed at identifying, classifying, and evaluating existing solutions for multi-view modelling of software and systems. To this end, we conducted a systematic literature review of the existing state of the art related to the topic. More specifically, we selected and analysed 40 research studies among over 8600 entries. We defined a taxonomy for characterising solutions for multi-view modelling and applied it to the selected studies. Lastly, we analysed and discussed the data extracted from the studies. From the analysed data, we made several observations, among which: (i) there is no uniformity nor agreement in the terminology when it comes to multi-view artefact types, (ii) multi-view approaches have not been evaluated in industrial settings and (iii) there is a lack of support for semantic consistency management and the community does not appear to consider this as a priority. The study results provide an exhaustive overview of the state of the art for multi-view software and systems modelling useful for both researchers and practitioners. Keywords Model-driven engineering • Multi-view modelling • Viewpoints • Views • Consistency 1 Introduction Conventional wisdom on Model-Based Development (MBD) suggests that separation of concerns in modelling is crucial to manage the sheer complexity of modern software systems [1]. In fact, software engineering problems intrinsically involve many domains, each with their own experts, notations, and tooling [2]. Thus, providing these experts with views of the system that are specifically tailored to particular tasks enables superior clarity and simplicity by letting Communicated by Dr. Jeff Gray.