In this paper, we use fractal dimensional analysis to investigate the Tamil Nadu rainfall dynamics. We analyze the time series data of Tamil Nadu rainfall (annual, south west and northeast) using Hurst exponent. We use the rescaled range (R/S) analysis to estimate the Hurst exponent for 110 years rainfall data. The result shows a varying degree of persistence over shorter and longer time scales corresponding to distinct values of the Hurst exponent. Our studies suggest that Hurst exponent(H) of the annual rainfall of Tamil Nadu is H=1 which predicts its periodic motion, for the southwest rainfall H=0.725 i.e. the time series covers more ?distance__ampersandsignlsquo; than a random walk and is a case of persistent motion and for the northeast rainfall H=0.5 the time series is purely random. Further we analysis the fractal dimension for the Tamil Nadu rainfall; however, the fractal dimension of the annual and southwest rainfall of Tamil Nadu decreases to 1, the process becomes more and more predictable as it exhibits ?persistence? behavior. The northeast rainfall fractal dimension D for the time series is 1.5, which indicates that there is no correlation between amplitude changes corresponding to two successive time intervals. Therefore, no trend in amplitude can be discerned from the time series and hence the process is unpredictable.