Abstract: An accurate knowledge of the evolutionary trends in energy consumption is essential for the orderly progress of the emission peak targets. In this paper, the grey system theory is employed to analyze the influencing factors of China’s energy consumption in depth, according to the grey comprehensive correlation degree. This approach allows the valuable information of energy consumption to be extracted accurately, while eliminating the influencing factors that are not highly correlated with energy consumption and have significant multicollinearity problems among the factors. It enables the effective influencing factors of energy consumption to be identified. The logarithmisation concept is incorporated into the grey GM（1,N） model, resulting in the construction of a logarithmised grey GM（1,N） model utilizing the identified influential factors. The model’s efficacy is then validated, and its capacity to accurately portray the trajectory of China’s energy consumption is subsequently demonstrated. The results of the study demonstrate that the primary factors influencing the consumption of coal and oil are industrial structure and technological level, respectively, while per capita income is the most effective factor influencing the consumption of natural gas and electricity. China’s total energy consumption is expected to follow an inverted U-shaped trend, reaching a peak of 6.7 billion tons of standard coal in 2031. It’s predicted that coal consumption will reach its peak at 3.3 billion tons of standard coal in 2027 and subsequently decline rapidly to 2.5 billion tons of standard coal by 2035. The consumption of oil is expected to reach a maximum of 1.1 billion tons of standard coal in 2026, after which it will begin to decline to approximately 700 million tons by 2035. The growth rate for natural gas consumption remains above 6%, reaching 1.1 billion tons of standard coal by 2035. The growth rate of electricity consumption is maintained at a level of above 4%, which will reach 2.1 billion tons of standard coal by 2035. China’s energy consumption structure is set to undergo a significant transformation. By 2035, the traditional pattern of coal consumption will have given way to a new and diversified structure comprising coal, oil, gas and electric power. This shift will see the proportion of high-carbon energy consumption decline to 49%, marking the beginning of a new era of green, low-carbon and high-quality development in China’s energy sector. A comprehensive correlation analysis in grey can accurately describe the correlation level between energy consumption and influencing factors, and thus facilitate the excavation of potentially useful information. The logarithmised grey GM （1, N） model, established based on effective influencing factors, has high prediction accuracy and reliable prediction results, which can provide a reference for the prediction of energy consumption trends in other regions.