During the past several years, the grid application executed same jobs on one or more hosts in parallel, but the recent grid application is requested to execute different jobs linearly. That is, the grid application takes the form of workflow application. In general, efficient scheduling of workflow applications is based on heuristic scheduling method. The heuristic considering relation between hosts would improve execution time in workflow applications. But because of the heterogeneity and dynamic nature of grid resources, it is hard to predict the performance of grid application. In addition, it is necessary to deal with user's QoS as like performance guarantee. In this paper, we propose a service model for predicting performance and an adaptive workflow scheduling strategy, which uses maximum flow algorithms for the relation of services and user's QoS. Experimental results show that the performance of our proposed scheduling strategy is better than common-used greedy strategies.