This paper presents a strategy for static images recognition, specifically, face recognition us- ing a new technique and classification method known as LAMDA (Learning Algorithm for Multivariable Data Analysis). Mainly, the strategy consists of 3 steps in model recognition and classification, the first one called pre-processing, it is responsible for applying filtering processes to adjust images, to facilitate un- derstanding, among others. The second step corre- sponding to feature extraction, to ensure getting the attributes of the image and they can be distinguished easily. Finally, the classification step that relates classes with the analyzed images using the LAMDA technique.