As 4G networks evolve toward full 5G deployment and beyond 5G (B5G) research begins, new vertical opportunities are being introduced in the context of intelligent transportation, power systems, smart-city urban operation, security services, etc. The diversity of the vertical requirements as well as their particular implementation in citywide locations will make it a real challenge to be able to assess or predict application performance for some of those verticals. In this article, we were motivated by the fact that because of the very nature of verticals and their interaction with a very large-scale telecommunications infrastructure, neither measurements nor small-scale simulations will be sufficient for application performance monitoring and prediction. To enable the assessment and prediction of verticals, so-called Quality of Experience (QoE), we propose a comprehensive framework for very large-scale simulation. The framework is based on the random generation of realistic key performance indicators (KPIs), which vary according to changes produced by the dynamics of urban systems. The probability distributions used for context-dependent random generation are built from samples taken from either “traditional” small-scale simulations or real local measurements. Finally, we present the framework’s key features and current roadblocks for an end-to-end widespread implementation.