Traditional collaborative filtering recommendation technology has lower accuracy and couldn't meet the actual needs. So we convert the recommendation problem into the classification problem. We introduce Logistic classification methods based on the collaborative filtering technology and determine whether the recommending units are recommendable according to personal feature of users and products. The result shows that the method could greatly improve the accuracy of recommendation under the premise to ensure recall.