Makeup plays a very important role in today's lifestyle for women. It gives a positive impact on the person's personality, self-esteem, and confidence. As there is a humongous variety of makeup products and lipstick is an unavoidable product whenever it comes to any makeup style. It could be any style, finishing, or brand. There is a large assortment of lipstick colors. In today's day and age, a customer does not have the time to go through every product. Also, if the best makeup style or lipstick is not being chosen, and the right product is not being applied according to the profession and event, based on age, it could lead to disastrous results. Hence, estimating how a particular lipstick color looks after applying the makeup requires high imagination and being well-versed in current fashion trends. Therefore, to obtain more comprehensive guidance for an individual, this Res. proposes ALRS, a computational system for lipstick recommendation for women through machine learning (using collaborative filtering technique). The sole purpose of ALRS is not only to recommend the right product. Instead, this intelligent machine system will recommend the accurate lipstick color considering various attributes such as customer's age, skin complexion, etc. (basically the demographic details). The customer's profession, which event/occasion the customer has to attend, and the ongoing makeup trends are also considered. [ABSTRACT FROM AUTHOR]