India contributes substantially to global malaria incidents. Vector dynamics is the significant determinant of malaria risk. Hence, knowledge on the interaction between rainfall, malaria cases and malaria vector density can be very useful for controlling malaria transmission. Kalahandi was screened for malaria cases, Anopheline vector density and their temporal relationship with rainfall. Epidemiological data was obtained from National Vector Borne Disease Control Programme, Odisha, India. Three years vector population study was carried out. Rainfall data was obtained from a database maintained by the Govt. of Odisha and was analysed using Univariate ANOVA and Pearson correlation co-efficient tests using R-prog. Malaria was found to be prevalent throughout the year attaining peak between July to August and another peak in December, amidst which the clinical malaria cases being recorded implied highest incidents in the month of July. The results estimated the seasonality of the population of An. culicifacies, An. fluviatilis and An. annularis over the region and determined the influence of rainfall on the vector population dynamics. Simple linear regression analysis suggested that at one month lag monthly rainfall (P=0.0007) was a significant meteorological factor. Rainfall seemed to be one of the best malaria predictors because of its positive correlation with proliferation of malaria cases in conjunction with An. culicifacies density making malaria a serious health issue in Kalahandi.