The Kenuli Symmetry Bridge introduces a novel, purely integer-based heuristic approach to the Riemann Hypothesis (RH). By leveraging discrete symmetry transformations (n → n + rev(n)), digital-root cycles (with emphasis on the 3-6-9 triplet), continued-fraction convergence adjustments, and light integration of GUE mean-spacing heuristics, the model predicts nontrivial Riemann zero floor values (a₀) and corresponding prime gaps with high empirical accuracy. Tested on available datasets up to heights of approximately 10³² (Odlyzko tables), the framework demonstrates increasing predictive precision as the index n grows into the billions and trillions, approaching near-perfect alignment in large regimes with minimal computational resources — no high-precision arithmetic or supercomputers required. This work stands in contrast to conventional methods that rely on heavy analytic machinery and massive computing power. The primary discovery and full intellectual property belong to Navoda Hasaranga Baddewithana, an independent Sri Lankan researcher. The framework is named in honor of the author’s daughter, Kenuli Tehansa Baddewithana, and is dedicated to her medical care and future well-being. All rights are reserved. Ethical use only. Misuse for harmful purposes is strictly prohibited.