Aim: This study aimed to compare respiratory microbiota composition and lung function parameters between smokers and non-smokers and to explore associations between microbial diversity indices and lung function. Material and Methods: A comparative cross-sectional study was conducted with 160 participants divided equally into smokers (n = 80) and non-smokers (n = 80). Sputum samples and nasopharyngeal swabs were collected for respiratory microbiota analysis using 16S rRNA sequencing. Lung function parameters, including Forced Vital Capacity (FVC), Forced Expiratory Volume in 1 Second (FEV1), FEV1/FVC ratio, and Peak Expiratory Flow (PEF), were assessed using spirometry. Statistical analysis included t-tests, Mann-Whitney U tests, and correlation analysis using SPSS 16.0. Results: Smokers demonstrated significantly lower lung function parameters across FVC, FEV1, FEV1/FVC ratio, and PEF (p<0.001). Microbiota analysis revealed decreased alpha diversity (Shannon and Chao1 indices) and increased beta diversity (Bray-Curtis dissimilarity) in smokers (p<0.001). Smokers also exhibited lower relative abundances of Streptococcus, Prevotella, Veillonella, and Neisseria compared to non-smokers (p<0.05). Correlation analysis showed a positive association between alpha diversity and lung function and a negative association between beta diversity and lung function indices. Conclusion: Smoking significantly impairs lung function, reduces microbial diversity, and alters respiratory microbiota composition. The observed correlations between microbial diversity and lung function suggest that microbial dysbiosis may play a role in smoking-induced respiratory damage, highlighting the potential for microbiota-targeted therapies in respiratory health management.