This article demonstrates the benefit of taking an explanation-based approach in the development of features for computationally supported systems used for linguistic analysis in forensic contexts. As a focal point it considers Other Language Influence Detection (OLID) as well as its related field of Native Language Identifcation (NLI). An explanation-based approach allows the forensic linguist to understand the implications of the presence or absence of features as they vary across the contexts and situations s/he might encounter. The authors present a qualitative framework for types of explanation and show how different types of explanations are needed to develop a full and rich language-influence feature set. The authors are not advocating a strict or inflexible typology of feature explanation but are seeking a richness of explanation at a variety of levels of analysis instead. This in turn can be developed into computational approaches, which the authors contend will therefore be stronger and more applicable to forensic casework contexts.