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Background: The prognosis of chronic kidney disease (CKD) typically requires longitudinal estimated glomerular filtration rate (eGFR) data, making risk stratification difficult at initial consultation. Furthermore, eGFR-based clinical decisions often overlook the critical factor of patient age. This study aimed to establish a simplified predictive model for progressive CKD and quantify the impact of clinical interventions. Methods: Utilizing a historical dataset (1988–2003) from the pre-renin-angiotensin system inhibitor (RASi) and pre-sodium-glucose cotransporter 2 inhibitor (SGLT2i) era, we developed heatmaps to predict the probability of reaching eGFR < 30 mL/min/1.73 m2 by age 80 years. The model also estimated the risk reduction from smoking cessation and pharmacological therapies. The predictive performance for age + eGFR was assessed using standard calibration and discrimination metrics, and clinical utility was evaluated using decision curve analysis across a range of threshold probabilities. Risk reclassification analyses compared age +eGFR-based categories with conventional eGFR-based stratification. Results: Regarding the risk of eGFR < 30 mL/min/1.73 m2 by age 80 years, simulations confirmed a correlation between age and eGFR. At age 40 years, an eGFR of ~57 mL/min/1.73 m2 indicated a 50% probability of progressing to CKD stage 4 by age 80 years. This threshold decreases to 53 and 48 mL/min/1.73 m2 at 50 and 60 years of age, respectively. Calibration and discrimination analyses demonstrated acceptable agreement between predicted and observed risks. Decision curve analysis showed that an age + eGFR threshold of approximately 115 primarily provided a net benefit at lower threshold probabilities, supporting intensified surveillance strategies, whereas an age +eGFR of 100 showed a positive net benefit across a broader range of thresholds, comparable to the conventional eGFR < 45 mL/min/1.73 m2 criterion. While proteinuria markedly increased risk, smoking cessation provided a 9.4–11.2% risk reduction. Combined RASi and SGLT2i treatment showed the greatest impact, reducing progression probability by 31.2–40.0% (e.g., reducing a 50.0% baseline risk to 32.1% in 40-year-old men). Conclusions: The age + eGFR rule represents a simple, clinically interpretable heuristic for age-adjusted risk stratification based on a single eGFR measurement and may offer potential clinical utility for guiding surveillance intensity and consideration of earlier intervention strategies. However, external validation is required before clinical application.