Objectives: This study aimed to construct a model based on different N6-methyladenosine (m6A) regulatory factors involved in reducing the risk of the development of cardiovascular diseases under conditions of aerobic exercise. Methods: We screened for significantly different expressions of m6A regulators from the GSE66175 dataset. Five candidate m6A regulators were identified using the random forest model to predict aerobic exercise-mediated fat loss and reduction of the risk of cardiovascular disease. A nomogram model was established for analysis, and the consensus clustering method was used to distinguish between the two m6A clusters (clusters A and B). The single-sample gene set-enrichment analysis method was used to assess the abundance of immune cells in the samples related to cardiovascular anomalies. We determined the relationship between the functions of 29 immune cells and m6A clusters. Results: Twelve significantly and differentially expressed m6A regulators in the control and aerobic exercise groups were screened out, and it was observed that METTL13 correlated positively with the expression levels of the YTH domain containing 1 (YTHDC1), YTH N (6)-methyl adenosine RNA binding protein 1, and leucine-rich pentatricopeptide repeat-containing. The fat mass and obesity-associated gene negatively correlated with YTHDC1 and the fragile X mental retardation 1 protein. The random forest and support vector machine models were used to screen the ELAV-like RNA binding protein 1 (ELAVL1), RNA binding motif protein 15B (RBM15B), insulin-like growth factor binding protein 1 (IGFBP1), Wilms tumor 1-associated protein (WTAP), and zinc finger CCCH-type containing 13 (ZC3H13) genes. Analysis of the line graph model and the results obtained using decision curve analysis revealed the efficiency of the model. Gene ontology enrichment analysis was used to analyze the m6A regulatory gene model, and the results suggested that it was associated with RNA splicing. The results obtained using the Kyoto Encyclopedia of Genes and Genomes enrichment analysis method suggests that the genes were associated with Alzheimer’s disease and neurodegeneration pathways associated with multiple diseases. The m6A regulatory gene model was associated with most of the immune cells infiltrating tumors and was also closely related to genes associated with lipid metabolism. Conclusions: The m6A regulatory factor plays an important role in reducing the risk of cardiovascular disease under conditions of aerobic exercise-assisted weight loss. It is also associated with the metabolic pathways of low-density lipoprotein, high-density lipoprotein, and triglyceride.