Climate variability is one of the problems facing the world today; particularly in Ethiopia. The problem coupled with poverty make the condition worse. This study analyzes the effect of climate variability on farmers’ vulnerability on different agro-ecological zones. The study was conducted in Legambo district using time series of rainfall and temperature data for a given period and cross-sectional survey data were conducted from 251 randomly selected farmers for vulnerability analysis. The coefficient of variation (CV), Inverse distance weighting (IDW), precipitation concentration index (PCI), and Standardized anomaly index (SAI) were used to analyze rainfall variability through MS-Excel. Mann Kendall’s (MK) and Sen’s slope were used to detect trends and magnitude of the changes in rainfall and temperature by using Modified MK package from R-studio. To calculate overall vulnerability analysis by selecting 48 sub-component indicators categorized in to twelve major-components and then in to three contributing factors of vulnerability were used livelihood vulnerability index (LVI) and LVI-IPCC approach for each Agro-ecological zones (AEZ) by using STATA V16 and MS-Excel. The CV of rainfall shows moderate inter-annual and Kiremt (June-September) and high variability in Bega (October-January) and Belg (February-May). The IDW shows that rainfall amount decrease from north-east to west in the annual and Kiremt season. The PCI shows uniform rainfall distribution in Belg and Bega, moderate rainfall concentration in Kiremt, and irregular annual rainfall distribution. The SAI perceived that the presence of inter-annual rainfall with greater variability ranges from extremely dry in midland in 2014 to extremely wet in cold highland in 2018, which were more number of negative anomalies than positive and inter-seasonal anomaly was proportional. The MK output presented a positive trend in annual, Kiremt, and Belg rainfall in cold highland and highland AEZs and a negative trend in Bega rainfall and midland annual and Kiremt rainfall decreasing significantly 10% level of significant. Annual and seasonal maximum and minimum temperature mostly warming trends were observed in all AEZs. The LVI result was 0.370, 0.337, and 0.285 in cold highland, highland, and midland AEZs, respectively. A similar trend was found with LVI-IPCC with score of 0.013, 0.010, and -0.005 for cold highland, highland, and midland AEZs, respectively. However, both LVI and LVI-IPCC results showed that the highest score number cold highland was the most vulnerable, and the least score number midland was the least vulnerable to climate variability effects. This finding helps establish better adaptation strategies to enhance farmers’ adaptive capacity to climate variability.