Gentrification refers to the displacement of lower-income residents due to rising costs spurred by wealthier newcomers, reshaping urban demographics and economies. This study analyzes Mexico City’s 16 municipalities using K-means clustering on 46 socioeconomic, infrastructural, and demographic indicators to classify gentrification intensity. Results show high-gentrification zones—characterized by increased hotels, restaurants, and crime rates—offer better healthcare and education but suffer from unaffordable housing (low ownership, high prices). Conversely, low-gentrification areas face poverty, poor literacy, and inadequate housing, reflecting systemic inequality. Moderate-gentrification clusters emerge as transitional zones with mixed traits. Principal Component Analysis (PCA) distilled patterns: the first component separates extreme (high/low) gentrification, while the second identifies intermediate cases. Notably, gentrification correlates not just with economic shifts but also cultural displacement and polarized access to opportunities. These insights highlight the need for inclusive urban policies—such as affordable housing mandates and community reinvestment—to mitigate displacement while fostering equitable development. The methodology offers a scalable framework for other cities grappling with similar urban transitions.