Chunking in Korean texts with only simple heuristic rules obtained through observation on the text shows a good performance similar to other machine learning methods<cite> [6]</cite> . Park et al. proposed a hybrid of rule-based and machine learning method to handle exceptional cases of the rules, to improve the performance of chunking in Korean texts [5,<cite> 6]</cite> . In this paper, we present how CRFs, a recently introduced probabilistic model for labeling and segmenting sequence of data [12] , can be applied to the task of chunking in Korean texts.