This study investigates urban well-being in New York City and Berlin using a combination of survey-based life satisfaction data, quantum wave modeling, and spatial econometric approaches. Unlike classical deterministic frameworks, our methodology captures both the expected level and the uncertainty of life satisfaction, revealing significant intra-urban heterogeneity. Empirical results show that income inequality, housing costs, social capital, and access to green space are key determinants of welfare, with spatial disparities persisting in NYC’s outer boroughs and Berlin’s Eastern districts. The quantum wave model outperforms traditional utility-based models, highlighting the importance of probabilistic approaches in urban welfare analysis. Policy simulations indicate that targeted interventions in housing affordability, environmental quality, and mobility can effectively raise average welfare and reduce inequality. The study provides actionable insights for urban planners and policymakers, emphasizing the need for distribution-sensitive and spatially aware strategies to enhance life satisfaction and urban resilience.