This study examines the long- and short-run asymmetrical effects of climate change on crop production by analyzing an annual time series from 1990 to 2019. In order to model the long-run and short-run cointegrations of a number of variables across time, as well as their causality directions, an ARDL (Autoregressive Distributed Lag) method was employed. The results of the study were also analyzed using a regression model in order to assess the reliability of the findings. As a preliminary result, a causal relationship between the variables, on a long-term basis, has been established using the Fully Modified Ordinary Least Squares (FMOLS), Canonical Cointegration Regression (CCR), and Vector Error Correction Model (VECM). The study found that crop production and carbon dioxide emissions in the country have a very strong relationship both on a short-term as well as a long-term basis, as well as showing a positive relationship between labor force, fertilizer use, and water availability over the long-term. A long-term analysis of the labor force, fertilizer use, and water availability shows a significant positive correlation between the three variables. As a result of the short-run study, several factors were positively and statistically significant, including carbon dioxide emissions, temperature, labor force, and fertilizer use. There was a significant influence of both climatic and non-climatic factors on Pakistan's crop production based on a paired Granger causality test. Based on the study's conclusions, Pakistan's policymakers must develop agricultural policies, strategies, and plans for the purpose of reducing carbon dioxide emissions, according to the conclusion of the study. Thus, by encouraging environmentally friendly farming methods, the country will be able to increase its efforts toward achieve sustainable agriculture. It is important for the country to promote environmentally friendly farming in order to achieve a sustainable agriculture industry.