The Saudi economy is driven by the energy sector which mainly derived from petroleum-based resources. Besides export, the Kingdom’s consumption of this resource showed a significant increase which linearly promoting CO 2 emission increment. Therefore, it is essential to model the Kingdom’s energy consumption to estimate the profile of her future energy consumption. This work explores modelling and multi-step-ahead predictions for energy use, gross domestic product (GDP), and CO 2 emissions in Saudi Arabia using previous data (1980–2018). The dynamic interrelationship of the variable’s nexus was tested using the Granger causality and cointegration method in the short-run and long-run. In the long-run, the models reveal an inverted U-shape relation between CO 2 emissions and GDP, validating Environmental Kuznets curve. When energy consumption is increased by 1%, there will be an increase in CO 2 emissions by 0.592% at constant GDP, and when GDP is increased by 1%, there will be an increase in CO 2 emissions by 0.282% at constant energy used. CO 2 emissions appear to be both energy consumption and income elastic in Saudi Arabia in the long-run equilibrium. Granger causality based on vector error correction method reveals unidirectional causality from income to CO 2 emissions, and bidirectional causality from CO 2 emissions to energy consumption and vice versa in the short-run. In the long-run, bidirectional causality from income to CO 2 emissions and vice versa and unidirectional causality from the used energy to CO 2 emissions were observed. Also, there is a bidirectional causality from GDP to energy used and vice versa in the short-run, meaning that GDP and energy consumption are interdependent. Saudi Arabia needs to increase energy infrastructure investments and increase energy efficiency by implementing energy management policies, reducing environmental pollution, and preventing the negative effect on economic growth. Graphical abstract