Distributed privacy preserving data mining tools are critical for mining multiple databases with a minimum information disclosure. We present a framework including a general model as well as multi-round algorithms for mining horizontally partitioned databases using a privacy preserving k Nearest Neighbor (kNN) classifier. Categories and Subject Descriptors: H.2.8 [Database Management]: Database Applications General Terms: Algorithms, Experimentation, Security