This study “Effects of Climate Change on Groundwater Resources in Kogi State using Water balance Method” was carried out to understand how change in climate condition affect the quantity aspect of groundwater. In order to achieve this goal, questionnaires, climate data and soil samples were collected during the field work. Questionnaires were used to assess inhabitants’ perception about climate change and its potential impact on groundwater. Responses from questionnaire administered were used to calculate a percentage of answers and then bar charts were plot for each question. Historical climate data were analyzed to confirm population perception about the change in climate condition. Descriptive statistic, box plot, trend analysis and bar charts were used to visualize the data distribution characteristics and displays the direction of the change. From climate data, monthly and annual aquifer recharge were estimated using water balance equation and then correlation and regression statistic were performed among parameter used for recharge estimation. Soil analysis using dry sieve analysis technique was implemented to appraise natural soil hydraulic conductivity or the rate of aquifer recharge. The results reveals that hand dug wells, boreholes, stream and rivers were the water sources mostly used in the study area. Respondents estimate that the rainfall amount is becoming low over years with variations in the start and end of raining season. For some respondents, the rainy season is becoming shorter with large amount of rainfall. Respondents also notice that the sun is now very hotter (86.7%) than before. Most of respondents (80%) cannot explain what climate change is but they believe strongly (95.6%) that climate is changing. Those change in climate according to them affect the groundwater quantity and quality observed through change in taste (42%), odor (40%), and color (53%). General upward trend was found in annual rainfall data and also intensification in amount of rain from one decade to another. Minimum and maximum temperature data displayed increase in mean value over year shows by time series plots. Monthly aquifer recharge computation reveal that it occurred between April to October with high amount of water recharge during the month of June, July and August. Annual aquifer recharge amount were strongly dependent on the amount of rainfall. Hydraulic conductivity estimated from grain size distribution analysis was characterized by low natural capability of soil to let water flow through it.