It is understood that children learn the use of grammatical categories in their native language, and previous models have only been partially successful in describing this acquisition. The present study uses an adaptation selection algorithm to continue the work in addressing this question. The input for the computer model is child-directed speech towards three children, ages ranging from 1;1 to 5;1 during the course of sampling. The output of the model consists of the input words labeled with a grammatical category. This output data was evaluated at regular intervals through its ability to correctly identify the grammatical categories of language of the target child. The findings suggest that the use of this type of model is effective in categorizing words into grammatical categories in both accuracy and completion.