The researchers developed a gender-specific method using machine learning to estimate body fat percentage. They created a dataset with 163 individuals and tested different regression methods. The results showed that the approach accurately estimated body fat percentage for both males and females, with low errors and high accuracy scores. This method could provide a cost-effective way to estimate body fat percentage without the need for expensive equipment like DXA scans.