  In this paper we present an approach for estimating the quality of machine
translation system. There are various methods for estimating the quality of
output sentences, but in this paper we focus on Na\"ive Bayes classifier to
build model using features which are extracted from the input sentences. These
features are used for finding the likelihood of each of the sentences of the
training data which are then further used for determining the scores of the
test data. On the basis of these scores we determine the class labels of the
test data.
