Today s competitive marketplace requires industries to understand the unique and particular needs of their customers. Software product line enables industries to create individual products for every customer by providing an interdependent set of features that can be configured to form personalized products. However, as most features are interdependent, users need to understand the impact of their gradual decisions in order to make the most appropriate choices. Thus, especially when dealing with large feature models, specialized assistance is needed to guide the users personalizing valid products. In this project, we aim using recommender system and search-based software engineering techniques to handle the product configuration process in large and complex product lines.