Translation Memory (TM) is a valuable tool that helps human translators in doing their job. TM consists of a collection of previously translated texts, called translation units, that may prove useful in the translation of new text. The main problem faced by translators who wish to take advantage of TM is that, although search tools do exist, there is no standardized way of effectively ranking search results. This thesis proposes a method for ranking TM search results together with a novel approach to efficiently finding common substrings that is used in the ranking process.