Problem: The goal of a software product line is to aid quick andquality delivery of software products, sharing common features.Effectively achieving the above-mentioned goals requires reuseanalysis of the product line features. Existing requirements reuseanalysis approaches are not focused on recommending product linefeatures, that can be reused to realize new customer requirements.Hypothesis: Given that the customer requirements are linked toproduct line features' description satisfying them: then the customer requirements can be clustered based on patterns and similarities, preserving the historic reuse information. New customerrequirements can be evaluated against existing customer requirements and reuse of product line features can be recommended.Contributions: We treated the problem of feature reuse analysisas a text classification problem at the requirements-level. We useNatural Language Processing and clustering to recommend reuseof features based on similarities and historic reuse information.The recommendations can be used to realize new customer requirements. © 2020 Copyright held by the owner/author(s).