Leptospirosis is a zoonotic bacterial disease that remains an important public health problem, especially in tropical developing countries. Some previous studies have revealed the outbreak of leptospirosis after heavy rain, but research determining its quantitative risks associated with rainfall in Thailand, especially at the national level, remains limited. The association between rainfall and leptospirosis was examined across 60 provinces of Thailand, and the heterogeneity of the estimated effects among provinces was also assessed. Monthly number of leptospirosis surveillance and meteorological data from 2007 to 2017 were obtained from the Bureau of Epidemiology and Thai Meteorological Department, respectively. A quasi-Poisson regression framework combined with the distributed lag non-linear model was used to estimate province-specific association between rainfall and human leptospirosis, adjusting for potential confounders. Province-specific estimates were then pooled to derive regional and national estimates using random-effect meta-analysis. The results found that the highest estimated risk of leptospirosis associated with rainfall was observed at the same month (lag 0). Using 0 cm/month of rainfall as a reference, the relative risks of leptospirosis associated with heavy (90th percentile), very heavy (95th percentile), and extremely heavy (99th percentile) rainfall at the national level were 1.0994 (95% CI: 0.9747, 1.2401), 1.1428 (95% CI: 1.0154, 1.2862), and 1.1848 (95% CI: 1.0494, 1.3378), respectively. The heterogeneity of the estimates was found among provinces ( I 2 = 27.1%, p -value <0.01), where northern and north-eastern regions were identified as the highest risk of leptospirosis associated with rainfall. In particular, relative risks of leptospirosis associated with extremely heavy rainfall in northern and north-eastern regions were 1.2362 (95% CI: 0.9110, 1.6775) and 1.2046 (95% CI: 0.9728, 1.4918), respectively. Increasing rainfall was associated with increased risks of leptospirosis, especially in the northern and northeastern regions of Thailand. This finding could be used for precautionary warnings against heavy rainfall.