As a global feature of fingerprint, orientation field is very important to automatic fingerprint identification system (AFIS). Establishing an accurate and concise model for orientation field will not only improve the performance of orientation estimation, but also make it feasible to apply orientation information into the matching process. In this paper, such a novel model for orientation field of fingerprint is proposed. We use a polynomial model to approximate the orientation field globally and a point-charge model at each singular point to improve the approximation locally. These two models are combined together by a weight function. Experimental results are provided to illustrate this combination model is more accurate and robust to noise compared with the previous works. Its applications are discussed at the end.