This paper presents a Trustworthy Services Selection Based on Preference Recommendation (TSSPR) method that assists users in selecting the right Web services, according to their own preferences. First, a group of recommenders that have similar preferences are found, and then the similarity rating is computed by using the Pearson correlation method. Second, filtering services based on the user’s recommending level, relative domain degrees, and similarity ratings can improve the quality of recommendations. Experimental results show that given an appropriate setting, this method can effectively solve the weaknesses of recommendation systems, such as sparseness, cold starts, and inaccurate recommendations.