This chapter sets out to contribute to invariance testing over and beyond the existing investigations through the modeling of differences in measurement instruments in international large-scale assessments (ILSAs). It starts with a review of the basic concept of measurement invariance and its challenges with regard to ILSAs. It then sets out to integrate measurement invariance evaluations with substantive insights into measurement bias. In other words, the chapter argues beyond the existing measurement invariance evaluation that a generic latent structural and measurement modeling or the simple structure of a common-factor model is unlikely to yield fully comparable scores within the contexts of ILSAs. Next, it provides a stepwise strategy for evaluating measurement invariance with a productive way of dealing with the unattainable ideal of scalar invariance. These kinds of strategies could help to integrate modern, less stringent approaches to measurement invariance by implementing substantive theories about target constructs and assessment processes in analyses, which could improve understanding of the nature of the sources of measurement invariance. It also presents an empirical example using ILSA data and discusses some general issues in evaluating measurement invariance across many groups along with considering limitations and strategies