Abstract: The study investigated the trend of climatic elements and its effect on vegetation cover in Adamawa state from 1988-2017. Pearson correlation coefficient was used to check the strength of relations between NDVI and the related climate elements (i.e., temperature, precipitation, relative humidity and sunshine hours) and regression analysis was further used to identify the effectiveness of each climate elements on vegetation cover. The result indicated that NDVI had a positive correlation with precipitation and temperature (p = 0.672) in Yola and Gyawana for three decades, followed with marginal negative correlation (p = 0.000) in the last three decades. Ganye in the same period had slightly stable precipitation with positive correlation (p = 0.005) while Mubi recorded remarkable decreased of precipitation slightly negative correlation (p = 0.109) but a slightly negative correlation with relative humidity and sunshine hours at Yala (p = 0.129), Gyawana (p = 0.015) and Ganye. Evaporation and temperature shows similar negative correlation in both study sites Yala (0.768; 0.129 0.263), Gyawana (0.015) and Ganye. Annual maximum temperature had noticeable increased during the study period in both study sites 2003 was recorded highest 43°C while 2000 was recorded lowest 31°C with no significant correlation in Yola (p = 0.201). Precipitation and temperature trend exhibited a positive slope of the model line indicating overall increased in precipitation and temperature with time in Yola, Gyawana and Ganye with positive relationship with NDVI (p = 0.672; 0.000; 0.005) while Mubi recorded remarkable decreased with negative relationship (p = 0.109). Evaporation, sun shine and relative humidity shows similar negative trend with low relationship in Yola and Mubi while sun shine trend increases in Ganye and relative humidity in Gyawana; it is concluded that based on the close relationship between NDVI and the major climate elements (Precipitation and Temperature) revealed in this studies, further investigations became necessary to investigate the vegetation dynamic responses to changes in the two major climate variables and establish quantitative relations between them.