Climate change has a devastating effect on food production by hampering the agriculture sector. This study aimed to analyze the impact of climate change and energy consumption on food production in Somalia using annual time series data spanning 1985–2017. This study employed the autoregressive distributed lag model (ARDL), impulse response function (IRF), and variance decomposition (VD). The empirical results of the study indicate that rainfall and energy consumption have constructive roles in enhancing food production both in the long- and short-run, whereas average temperature is inconsequential in the long run. Furthermore, the rural population measured for agricultural labor, and capital significantly reduce food production in the long run. Besides, the VD results show that average rainfall, temperature, and energy consumption explain 26 %, 28 %, and 8.99 % of the historical fluctuations in food production, respectively. Moreover, the result of the IRF revealed that food production responds heterogeneously to the shocks that occur in rainfall. A 1 % standard deviation shock in average rainfall leads food production to decrease from periods 1 to 5, but from period 6, the response turns positive. Food production responds positively to a 1 % standard deviation shock in temperature in all periods except Period 7. Based on the empirical findings, this study recommends the implementation of policies related to the reduction of environmental pollution, deforestation, and agricultural adaptation to climate change.