The impacts of climate change in agriculture is a growing concern. The agricultural sector plays a significant role in North Dakota's (ND) economy, and spring wheat contributes most to the economy. This study focuses on assessing possible impacts of three climate variables on spring wheat yield in ND by building regression model. The trend of average minimum temperature, average maximum temperature, average precipitation and spring wheat yield was analyzed using Mann-Kendall test for 86 years. The study was conducted by dividing ND into 9 divisions. Increasing trend was noticed for 6 divisions for average minimum temperature and average precipitation during growing season. Northeast and Southeast division showed the strongest increasing trend for average minimum temperature and average precipitation, respectively. Eastcentral division had the most decreasing trend for average maximum temperature. Significant relationship was established between spring wheat yield and climatic parameters. The regression model was tested for forecasting accuracy.