With the maturity of cloud computing theories and technologies, more and more cloud services have been gaining enormous momentum, so how to establish highquality cloud services has become a critical problem in the field of cloud computing. QoS rankings provide users with valuable information for making optimal cloud service selection from a set of functionally equivalent service candidates. To obtain QoS values of the cloud service, it is indispensable to invoking the realworld candidates of the cloud service. In order to avoid huge time consumption and expensive resource waste, we propose a QoS prediction approach based on timeaware ranking. Unlike traditional QoS value prediction, the proposed prediction method based on QoS ranking similarity can examine the order of services for a particular user. The ranking similarity is calculated by timeweight, and combining with time preference for synthetic similarity the topk neighbours are selected to provide QoS information support for the evaluation. Experiments based on WSDream, a realworld dataset, show that the QoS prediction method based on timeaware ranking has better prediction accuracy.