It is labor-intensive to manually verify the outputs of a large set of tests that are not equipped with test oracles. Test selection helps to reduce this cost by selecting a small subset of tests that are likely to reveal faults. A promising approach is to dynamically mine operational models as potential test oracles and then select tests that violate them. Existing work mines operational models from verified passing tests based on dynamic invariant detection. In this paper, we propose to mine common operational models, which are not always true in all observed traces, from a set of unverified tests based on mining predicate rules. Specifically, we collect values of simple predicates at runtime and then generate and evaluate predicate rules as potential operational models after running all the tests. We then select tests that violate the mined predicate rules for result inspection. Preliminary results on the Siemens suite and the grep program show the effectiveness of our approach.