In this study, we develop data-based word juncture models, which account for the pronunciation variations at word boundaries, as an optional form of phonological rules. We used the American English TIMIT database. Issues in generating the models and using them in a continuous recognition task are discussed. A comparison is given between the coverage of the pronunciation variations by the models and by a set of phonological rules. There is a fairly good agreement between the models and the rules in predicting the pronunciation variations, whereas the models cover a larger set of variation phenomena. Furthermore, use of the models improved recognition performance.