This study aimed to analyze the relationship between building density and urban livability in the neighborhoods of District 9 in Mashhad, Iran. The research method is mixed (quantitative-qualitative) and descriptive-analytical. Data were collected using questionnaires (401 samples), objective documentary data, and within a Geographic Information System (GIS) environment, and were analyzed using Analytic Hierarchy Process (AHP), Simple Additive Weighting (SAW), and notably, Logistic Regression. Findings revealed that the relationship between density and livability is non-linear, following an S-shaped (logistic) curve, with density explaining only about 18.8% of livability variations. An optimal range for density was identified between 280% and 400%, where the benefits of density such as economies of scale and better access outweigh its disadvantages. Furthermore, increased building density was associated with a reduction in per capita public services, especially green space. Neighborhood prioritization showed that "Reza Shahr" neighborhood had the highest, and "Valiasr" neighborhood had the lowest level of livability. The research innovation lies in integrating subjective and objective assessments of livability at the neighborhood scale and employing a combined model in the Iranian urban context. The key conclusion is that building density can lead to improved quality of life only if accompanied by balanced development of urban infrastructure and services. Future planning should focus on "optimal density coupled with services."