The occurrence of rainfall extreme events leads to several environmental, social, cultural, and economic consequences, heavily impacting agriculture. The analysis of climate extreme indices at the municipal level is of the uttermost importance to the overall study of climate variability and regional food security. Corn, bean, and cassava are among the most cultivated temporary subsistence crops. Thus, the objective of this study was to analyze the relationship between subsistence agriculture productivity and the behavior of rainfall extreme indices in the Rio Grande do Norte state in the period from 1980 to 2013. We used the dataset provided by Xavier (2016) and the climate extreme indices obtained through the Expert Team on Climate Change Detection and Indices. Crop productivity data were retrieved from the Municipal Agriculture Survey from the Brazilian Institute of Geography and Statistics system. The methodology evaluated the behavior and the relationship between agricultural productivity time series and extreme precipitation indicators. We applied the following statistical techniques: descriptive analysis, time series trend analysis by the Mann-Kendall test, cluster analysis, and analysis of variance to check for equal means between identified groups. Cluster analysis was considered an adequate tool for the comprehension of data spatial distribution, allowing the identification of five homogenous subregions with different precipitation patterns. Rainfall extreme indices allowed the analysis of regional conditions regarding consecutive dry days, annual precipitation in wet days, and heavy rainfall. Trends were identified in these indices and they were significantly correlated with dryland crops productivity, indicating a direct relationship between water availability and regional agroclimatic stress.