Abstract: A “Linguistic Complexity Tool” uses Machine Learning (ML) based techniques to predict “source complexity scores” for localization of source language assets or resources (i.e., “source content”), or subsections of that content, to provide users with predicted levels of difficulty in localizing source content into target languages, dialects, or linguistic styles. These predicted source complexity scores provide a number of advantages, including but not limited to, improved user efficiency and user interaction performance by identifying source content, or subsections of that content, that are likely to be difficult or time consuming for users to localize. Further, these source complexity scores enable users to modify source content prior to localization to provide lower source complexity scores, thereby reducing error rates with respect to localized text or language presented in software applications or other media including, but not limited to, spoken or written localizations of the source content.