<p>It remains uncertain whether patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and bacterial lower respiratory tract infections (LRTIs) could similarly benefit from β-lactam and macrolide antibiotics therapy as community-acquired pneumonia (CAP) does. In this study, we compared the clinical success rates of piperacillin/tazobactam (TZP) monotherapy versus its combination with erythromycin lactobionate injection (Ery) in patients with AECOPD and bacterial LRTIs and developed a machine learning (ML) model to predict treatment outcomes. The patients with AECOPD and bacterial LRTIs received antimicrobial therapy with either piperacillin-tazobactam (TZP) alone or TZP in combination with Ery. Inverse probability of treatment weighting (IPTW) was performed between the two groups. Subsequently, a stacking ensemble learning (SEL) model was developed and deployed as a web application to simultaneously predict clinical outcomes for both treatment options. The result demonstrated that TZP combined with Ery significantly reduced the incidence of clinical treatment failure compared to TZP monotherapy (14.00% vs. 19.75%; OR, 0.66; 95% CI, 0.49–0.89; <i>P</i> = 0.006). In an independent test set, the SEL model demonstrated strong performance across multiple metrics, including ROC-AUC (0.71), recall (sensitivity) (0.72), and accuracy (0.69). Finally, a web application based on the SEL was developed (<a href="http://106.12.146.54/">http://106.12.146.54/</a>). This study demonstrated that the addition of Ery to TZP significantly reduced clinical treatment failure in patients with AECOPD and bacterial LRTIs. This finding suggests that combination therapy may offer a clinical benefit in this patient population. Furthermore, an SEL model was developed to predict treatment outcomes for both regimens, providing a potential tool for future clinical decision-making and personalized treatment.</p>