As the middle class in developing nations like ours expands rapidly, the use of recommender systems in the insurance industry is becoming a crucial new field of research. Recommendation systems designed for online platforms like e-commerce, movies, and songs are typically constructed using extensive datasets with the goal of suggesting the most suitable options. However, insurance products possess special attributes that require a different methodology. This paper presents a novel recommendation method for life insurance that aims to provide users with the ability to make informed decisions when choosing personalized and unbiased life insurance products. This paper proposes design and development of ‘Insurance_4_YOU’, a life insurance recommendation system on the basis of extensive preference specifications by the user. It implements the hybrid FUCOM-TOPSIS method of the MCDM domain to determine personalized insurance policies for the user on the basis of priorities and individual requirements. The prototype is validated by taking live dataset through a designed desktop application that is tailored to provide a user-friendly environment of preference specifications.