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Air pollution is one of the leading environmental risk factors affecting human health worldwide. Fine particulate matter (PM2.5) is considered particularly harmful due to its ability to penetrate deep into the lungs and enter the bloodstream, increasing the risk of respiratory diseases. This study aims to analyze the relationship between PM2.5 concentration and respiratory disease incidence in Kyrgyzstan using data visualization techniques. The dataset was obtained from two main sources: annual PM2.5 concentration data were collected from the World Health Organization (WHO), while respiratory disease statistics were acquired from the National Statistical Committee of the Kyrgyz Republic. The data cover the period from 1990 to 2024. After preprocessing and merging the datasets, various visualization and statistical techniques were applied using Python libraries, including Pandas, Matplotlib, and Seaborn. Trend analysis revealed a significant increase in PM2.5 levels after 2010, which coincided with a rise in respiratory disease cases. Correlation analysis showed a moderate positive relationship between PM2.5 concentration and respiratory disease incidence (r = 0.56). Regression analysis further confirmed that higher pollution levels are associated with increased numbers of respiratory disease cases. Although the correlation is not strong, the results indicate that air pollution is an important contributing factor to respiratory health outcomes. The moderate strength of the relationship may be explained by delayed health effects and the influence of additional factors such as lifestyle, seasonal infections, and healthcare access.