With the trend toward personalization and diversity in customer demand, enterprises are faced with the challenge of how to respond to customer demand quickly and provide personalized product service solutions. To locate personalized product service solutions accurately, a personalized product-service configuration method based on trust degree and forgetting curve is proposed. First, the method introduces the trust degree and time weight into the calculation of preference similarity and score similarity. Then, it integrates user similarity and scheme similarity to reduce the impacts of data sparsity and cold starts on rating prediction. Finally, by comparing it with existing methods, the proposed method can improve the accuracy of product service scheme configuration.