This paper proposes an approach to detect Ponzi schemes implemented in smart contract on Ethereum blockchain by using data mining and machine learning methods. The experimental results show that the proposed approach can achieve high accuracy for practical use. More importantly, the approach can be used to detect Ponzi schemes even at the moment of its creation. By using the proposed approach, we estimate that there are more than 400 Ponzi schemes running on Ethereum.