<p>The Wnt/β-catenin signaling pathway is a key regulator of cellular activities and has implications for various diseases. This study explored the ability to predict the bioactivities of compounds against the peroxisome proliferator-activated receptor γ (PPARγ), paving the way to develop PPGBioPred, a user-friendly webserver to modulate this pathway. The research employs computational methodologies, particularly quantitative structure–activity relationship (QSAR) models, to understand the bioactivity of compounds. The study evaluated the efficacy of twelve categories of fingerprint descriptors for model development and used the Gini index to reveal the molecular features crucial for the studied bioactivity of PPARγ. The resulting high-performing models – achieving external R² values of 0.57 (IC₅₀) and 0.62 (EC₅₀), and classification MCCs of 0.74 (IC₅₀) and 0.70 (EC₅₀) – are deployed on PPGBioPred, providing a robust and translational tool for virtual screening. These models contribute significantly to the understanding of the structure‒activity relationship of PPARγ and the ability to predict the bioactivities of certain chemical compounds against the aforementioned target. This study underscores the potential of computational methodologies in supplementing experimental research in drug discovery. These findings pave the way for the development of effective drugs targeting PPARγ, highlighting the potential of these proteins in the treatment of diseases affecting multiple organs.</p>