Drought is a natural phenomenon, which occurs with decreasing precipitation relative to the medium or long-term conditions.This phenomenon begins slowly, spread slowly and heavily affects all aspects of human activities,and is dominated in a vast region of Iran.The dominant climatological pattern in a region may affect another region, although there is a climate disparity between different regions, especially the tropics and outlying regions, there is a systematic relation s hip between them.Teleconnection is also a new branch of synoptic climatologywhich recognizes the relationships between phenomena and climatic elements in remote of locations.In this research, the relationship between Oceanic- Atmospheric and drought indices in Iran was investigated.For this purpose, rainfall data from 37 synoptic stations in Iran with at least 30 years of record up to 2015 were used. First, by calculating the SPI drought indicator timescales, presence or absence of simultaneous or lagged relationship between the SPI index and Oceanic-Atmospheric oscillations was estimated using MINITAB16 and 16 softwares. The monthly series of Oceanic-Atmospheric oscillation data and SPI in 1, 3, 6, 9, 12, 15, 18, 24 and 48-month timescales were considered from 1951 to 2015.Then the spearman correlation coefficient (for simultaneous status) and Cross Correlation Function (for lagged effects) between different SPI series and Antarctic Oscillation(AAO), Arctic Oscillation(AO) , Atlantic Multi-decadal Oscillation(AMO), North Atlantic Oscillation(NAO), ENSO indices NINO1.2, NINO3, NINO3.4, NINO4, SOI and the Western Mediterranean Oscillation(WeMo) index were analyzed for all stations.1,2,3,4,5,6,12,24,48 months lag time was considered for significant asynchronous relationships. The next step, box plots for Cross Correlation Function coefficients were plotted.Finally, regression equations, between different SPI timescales in simultaneous or lagged status (i.e 1,3,6,9,12,24,48 lag times) of Ocean- Atmospheric index were calculated. Results of relationship between indices and spatial distribution maps of Oceanic- Atmospheric indices effects in Iran was showedsimultaneous relationship between SPI in Western, Southwest and North of Iran with NINO1.2, NINO4 and AMO and lagged relationship between SPI with AMO indices and NINO4 and NINO3.4 at stations in northern Iran.Relationship between AAO, AO, SOI, WeMo indices with SPI values for East and South- East stations of Iran in simultaneous and the relationship between AO, NAO, SOI, WeMo, AAO, with SPI at all stations in lagged times showed a weak correlation.The AMO showed the highest degree of association in the analysis of regression equations at Bushehr station. It seems that this indicator can be effective in predicting climate conditions, drought and crisis management in Iran.Further studies on the relationship between other Ocean- Atmospheric oscillations with other climatic phenomena such as floods in affected areas are strongly recommended. Keywords: Drought, Multivariate Regression, Oceanic-Atmospheric Oscillations, Correlation, Iran, MINITAB16, .16 .