Machine translation has always been interesting to people since the invention of computers. Most of the research has been conducted on western languages such as English and French, and Turkish and Turkic languages have been left out of the scene. Machine translation between closely related languages is easier than between language pairs that are not related with each other. Having many parts of their grammars and vocabularies in common reduces the amount of effort needed to develop a translation system between related languages. A translation system that makes a morphological analysis supported by simpler translation rules and context dependent bilingual dictionaries would suffice most of the time. Usually a semantic analysis may not be needed. This thesis presents a machine translation system from Turkish to Crimean Tatar that uses finite state techniques for the translation process. By developing a machine translation system between Turkish and Crimean Tatar, we propose a sample model for translation between close pairs of languages. The system we developed takes a Turkish sentence, analyses all the words morphologically, translates the grammatical and context dependent structures, translates the root words and finally morphologically generates the Crimean Tatar text. Most of the time, at least one of the outputs is a true translation of the input sentence.