Microbial resistance has traditionally been interpreted through reductionist frameworks emphasizing isolated genetic mutations or clinical antibiotic exposure. This study advances a non-empirical theoretical investigation grounded in integrative conceptual modeling to reconceptualize resistance evolution as a cross-scale, eco-evolutionary phenomenon. A multi-scale analytical framework was constructed to synthesize stochastic mutation supply, horizontal gene transfer, metabolic rewiring, proteostasis regulation, environmental heterogeneity, and anthropogenic chemical pressures into a unified systems architecture. Structured theoretical synthesis and boundary-condition analysis were employed to test internal coherence and cross-context stability. The model demonstrates that resistance emerges as a metastable adaptive state maintained by feedback loops linking molecular mechanisms, community-level interactions, and physicochemical gradients across environmental compartments. Disinfectant exposure, nutrient enrichment, wastewater co-selection, and climate variability were incorporated as dynamic modulators of selective intensity. The resulting framework exhibits explanatory integration, cross-scale generalizability, and predictive plausibility under fluctuating selective regimes. By situating microbial resistance within interconnected ecological and evolutionary systems, this study provides a robust theoretical platform capable of guiding future simulation-based modeling and empirical corroboration within the One Health continuum.