The paper introduces a universal model for mobility and migration patterns, addressing the limitations of the gravity law, which has been widely used but lacks rigorous derivation and suffers from analytical inconsistencies. The authors propose a stochastic process that captures local mobility decisions, leading to an analytically derived radiation model that predicts commuting and mobility fluxes based solely on population distribution. This model is parameter-free and can be applied in areas with limited mobility data, improving the accuracy of predictions for various phenomena, including long-term migration, communication volume, and commodity flows. The radiation model resolves key issues with the gravity law, such as the need for adjustable parameters, systematic predictive discrepancies, and the inability to account for fluctuations in travel numbers. The model's performance is validated through comparisons with real-world data, showing superior agreement with observed commuting patterns and other mobility measures. The authors also explore the model's generality by testing it on different socio-economic phenomena and demonstrate its ability to uncover hidden self-similarities in human mobility.The paper introduces a universal model for mobility and migration patterns, addressing the limitations of the gravity law, which has been widely used but lacks rigorous derivation and suffers from analytical inconsistencies. The authors propose a stochastic process that captures local mobility decisions, leading to an analytically derived radiation model that predicts commuting and mobility fluxes based solely on population distribution. This model is parameter-free and can be applied in areas with limited mobility data, improving the accuracy of predictions for various phenomena, including long-term migration, communication volume, and commodity flows. The radiation model resolves key issues with the gravity law, such as the need for adjustable parameters, systematic predictive discrepancies, and the inability to account for fluctuations in travel numbers. The model's performance is validated through comparisons with real-world data, showing superior agreement with observed commuting patterns and other mobility measures. The authors also explore the model's generality by testing it on different socio-economic phenomena and demonstrate its ability to uncover hidden self-similarities in human mobility.