The present study aims to evaluate customer satisfaction with the recommendation algorithm used by Netflix. Online streaming platforms have revolutionized the way people consume media content. With the multiplication of choices and the abundance of content, it has become difficult for users to find the materials they are interested in watching. To address this problem, recommendation algorithms have been developed to suggest the content that the user is most likely to find entertaining. The research is conducted through structural modeling equations and data analysis, with the use of data from 274 Netflix users. The results show a positive relationship between personalization, use of search engine, homepage usefulness and satisfaction from using Netflix’s recommendation algorithm. The results of this research contribute to our understanding of customer satisfaction with the recommendation system of online streaming platforms.