Background and Objective: Chronic Obstructive Pulmonary Disease (COPD) remains a critical global health challenge, char-acterized by high morbidity, mortality, and healthcare costs. Current guidelines may overlook pa-tients who present with only one moderate exacerbation or frequent short-acting beta-agonist (SABA) use. Building on findings from the Seleida study, this research refines the criteria for poor COPD control to include these patients, aiming to improve early identification of high-risk cases in primary care. Methods: A retrospective, multicenter study was conducted using data from 110 COPD patients in Spain. Poor control was redefined as having at least one moderate exacerbation or using three or more SABA inhalers annually. Key predictors, such as SABA/short-acting muscarinic antagonist (SAMA) inhalers and antibiotic prescriptions, were identified using logistic regression and LASSO regular-ization to enhance predictive accuracy. Results: The model demonstrated excellent predictive performance with an AUC-ROC of 0.978, sensitivity of 92.86%, and specificity of 87.50%. Key predictors effectively identified high-risk patients, facili-tating timely interventions. Although the variable ‘daily inhalation frequency’ (categorized as 1 vs. >1 inhalation/day) showed that patients using a single inhalation daily had significantly better control than those requiring multiple doses (p = 0.018), it was excluded to avoid model overfitting. Conclusions: By refining the criteria for COPD control to include patients with at least one moderate exacerbation or frequent SABA use, this model provides a practical tool for early risk stratification in primary care, particularly in resource-limited settings. Early identification of high-risk patients can reduce hospitalizations and healthcare costs, supporting a proactive approach to COPD management. Further validation in larger cohorts is essential to confirm its broader applicability.