For almost 33 years, the Wolfram Language is a major computation and programming environment for millions of researchers, educators, students, and many other categories of creative people [1,2]. It o®ers to everyone the possibility to easily apply the most advanced computations and knowledge even in areas that seem to be extremely far from programming, numeric, symbolic, and technical computations. In this work we present an illustration how the Wolfram Language, and Mathematica System, can be used to investigate poetry and prose, translations of literary works to other languages, and evaluation of translation quality. First, we are starting from computation of some numerical characteristics of works in the original languages, and their translations into other languages, e.g., from Romanian to English, French, and Russian. Evidently, a good translation must preserve most characteristics of the original works. Is this so in reality? To make more objective conclusions, we apply some graphical, image, and sound tools. But we can use also some advanced mathematical tools such as the interpolation, and the curve ¯tting. Based on interpolation-functions (or ¯t-functions) that correspond to original works and their translations, we can evaluate good translation-works as ones for which interpolation functions (¯tfunctions) di®er insigni¯cantly from the interpolation-functions (¯t-functions) of the original works and may be very close one to other if the parallel mathematical (geometric) translation is applied. Second, we use Machine Learning to train a function that may recognize poetry and prose texts, that may ¯nd text's author, too. Should we train a function for every language, or it is enough to train one function for all languages?May a trained function have a \polyglot" feature? If the trained author-function \understand" more than one language, may it be applied to evaluate good worktranslation? Should the trained author-function understand who is the original language author of translated work? Our work presents not only answers to the above questions, but it highlights a series of other interesting subjects, and the answers, and comments to them. The ¯nal discussion and conclusions may be seen as a good starting point to an interesting area of research: computational recognition of the original language author for a translated work.