The association between meteorological parameters and dengue patients is a growing public health concern worldwide. This paper investigated the relationship between meteorological parameters and dengue cases in Bangkok from 2003 to 2016. Parameters of meteorology and dengue cases were collected from the Thai Meteorological Department and the Ministry of Public Health, respectively. Principle component analysis (PCA), Poisson Regression Model (PRM), and Mann-Kendall (MK) were applied. PCA was applied to variables affecting the number of dengue patients. PRM is utilized for considerable parameters. The dependent factors are dengue patients, while meteorological parameters are dependent parameters. The overall results of dengue cases show a positive correlation with Tmin. From the rainy season to the early winter months (July to December), dengue patients displayed the maximum probabilities of the incidence of new cases throughout the year. The tendencies of seasonal and annual dengue patients were significant at 1% and 5%. Another finding was that for each count of Tmax and Tmin from 1 to 10 °C, Tmax decreased in the number of dengue patients from −34.43% to −98.53%, while Tmin increased from 19.72% to 504.96%. However, for every 50–500 mm change in Rain, dengue cases had a mean drop (−2.47% to −22.12%). Therefore, Tmin was a suitable predictor in Bangkok’s rising number of dengue patients. This result is to inform the organization, supplying substantial evidence to share with people for protection.