<p>The question of how to reconstruct reasoning expressed non-verbally has recently attracted considerable attention in the research on multimodal argumentation. However, the dominant approaches to studying multimodal artifacts have rarely explicitly connected multimodality research and argumentation theory. In this paper, I respond to this challenge by proposing a multimodal argument reconstruction (MAR) model, which merges the two disciplines. The model allows the analyst to translate the reasoning expressed in various semiotic modes into the meta-language of propositions. In this way, different forms of communication are treated on par. To explain the mechanism behind the model, firstly, I distinguish the pieces of information necessary to formulate a speech act. I suggest that at least two speech acts and an indication of a discursive-causal relationship between them are needed to express a full argument. Secondly, I use multimodality research to describe how the necessary information is inferred from semiotic content. I refer to two logics rooted in discourse semantics: logic of information content and the glue logic. Afterward, to demonstrate how the MAR model can be used in practice, I present a sample analysis of an anti-Trump poster from 2016. Finally, I address the benefits of using the model as well as perspectives for its further development.</p>