A good indicator of whether a person really knows the context of language is the ability to use in correct order the appropriate words in a sentence. The “scrambled” words cause a meaningless and ill formed sentences. Since the language model, is extracted from a large text corpus, it encodes the local dependencies of words. The word order errors usually violated the syntactic rules locally and therefore the N-grams can be used in order to fix ill-formed sentences. This paper presents an approach for repairing word order errors in text by reordering words in a sentence and choosing the version that maximizes the number of trigram hits according to a language model. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The comparative advantage of this method is that works with a large set of words, and avoids the laborious and costly process of collecting word order errors for creating error patterns.