Interestingly enough, there was an article about this exact topic (more or less) on slashdot recently. Here's a link to the slashdot story, the scientific article it refers to, and MIT news article about the topic.
The abstract of the scientific article is:
In this paper we propose a method for the automatic decipherment of lost languages. Given a non-parallel corpus in a known related language, our model produces both alphabetic mappings and translations of words into their corresponding cognates. We employ a non-arametric Bayesian framework to simultaneously capture both low-level character mappings and high-level morphemic correspondences. This formulation enables us to encode some of the linguistic intuitions that have guided human decipherers. When applied to the ancient Semitic language Ugaritic, the model correctly maps 29 of 30 letters to their Hebrew counterparts, and deduces the correct Hebrew cognate for 60% of the Ugaritic words which have cognates in Hebrew.
Of course, this assumes that you know what language your unknown language is related to. If it is made up, it's probably worth knowing what languages its author knows and/or speaks.
The tool is probably available from the authors. It does not appear on Benjamin Snyder's web page, though other tools do.
On the other hand, if the text is cryptographically encoded (well) then you'll have a hard job of decrypting it. The field of cryptanalysis or 'code-breaking' deals with that topic.