<p>This study evaluated the effects of smog on airborne microbial load and antimicrobial resistance (AMR) pattern of <i>Staphylococcus</i> species in Lahore, Pakistan. The ten urban locations were sampled in November 2024–March 2025 by settle plate method to monitor airborne microbial load monthly. The isolated strains were identified morphologically, biochemically and by the 16S rRNA gene sequencing, while the Kirby–Bauer disk diffusion assay was used to determine susceptibility to a panel of commonly used antibiotics. In order to determine relationships between AQI, temperature and bacterial counts, the statistical tests, <i>i.e.</i>, Spearman’s rank correlation, Kruskal–Wallis tests and multiple linear regression, were conducted. The comparison of the microbial load showed that the highest bacterial count was found in the months of November and December with high smog intensity, where the CFU counts were found highest (<i>χ</i>² = 15.32, <i>p</i> = 0.0041), whereas the lowest counts were recorded during the months with a better air quality or low smog intensity. There was a moderately positive relationship between AQI and total microbial load (<i>r</i> = 0.41). Among the total number of <i>Staphylococcus</i> isolates, 40% were found to be multidrug resistant (MDRs). These results showed that smog-related air pollution can contribute to high microbial counts in air and can promote the spread of antibiotic-resistant bacteria in the air. The findings indicated the necessity of combining air quality monitoring systems with microbial surveillance, especially in smog-affected cities.</p>