Named Entity Recognition involves automatically identifying and classifying entities such as persons, places, and organizations, and it is a very important task in Information Extraction. Conditional Random Fields is a probabilistic method for structured prediction, which can be used in this task. This paper presents the use of Conditional Random Fields for Named Entity Recognition in Portuguese texts considering the term classification obtained by a Local Grammar as an additional informed feature. Local grammars are handmade rules to identify named entities within the text. The Golden Collection of the First and Second HAREM considered as a reference for Named Entity Recognition systems in Portuguese were used as training and test sets respectively. The results obtained outperform the results of competitive systems reported in the literature.