The body shape of the lower limbs plays a crucial role in the design of functional pants for elderly female adults. With advancing age, the body shape of elderly individuals gradually changes. This study aims to classify and analyze the lower body shapes of Chinese women aged 60–80 using anthropometric data. The research data were collected from 345 women in Zhejiang Province. This paper proposes a lower limb body shape classification method based on K-mean cluster analysis. Through factor analysis and correlation analysis, it was found that height, waist circumference, and the hip-to-waist ratio are the key dimensions for representing lower body shapes. Using the K-means cluster analysis method, the lower body shapes of elderly women were classified into five body types which are xs, s, m, l and xl. The results indicate that the K-mean cluster body classification method can be more accurately reflect body information without increasing the number of body shape types. The elderly body shapes obtained from this research are founded to be classified into three groups: abdominal protrusion, barrel-shaped, and slim. Compared to the national standard for women’s clothing sizes, elderly women tend to have larger waist circumferences, and higher hip circumferences. Anthropometric data is the basis of body size and shape identification, and body classification is a necessary prerequisite for the development of garment size system. These research findings will provide valuable references for the pattern design of lower body clothing for elderly women, the development of new sizing systems, and related industries.