Atherosclerosis is an underlying cause of cardiovascular diseases (CVD) which account for most deaths worldwide. Use of diverse preclinical models of atherosclerosis has been implemental in understanding the underlying mechanisms, the implicated cell types, the genes and the molecules at play in the onset and progression of atherosclerotic plaques. Although significant research advancements have been made, further research is necessary to delve into factors influencing plaque types, site preference within the vasculature, interactions with adjacent tissues (liver, pancreas and perivascular adipose tissue), inflammation and sex-based disparities, among others. The conventional low throughput methodologies which concentrate on individual cells, genes or metabolites are inadequate to tackle the complex and heterogeneous nature of atherosclerosis. With recent advancement in multi-omics and bioinformatics, research approaches have illuminated a clearer understanding of atherosclerosis. Consequently, these advancements pave the path to design novel therapeutics to complement currently approved lipid-lowering and other effective treatments. In this article, we summarize and critically evaluate the findings derived from recent high throughput single- or multi-omic studies conducted in animal models of atherosclerosis. We also delve into the challenges associated with using experimental animals to model human atherosclerosis and contemplate the essential enhancements needed to better mimic human conditions. We further discuss the requirement of establishing a structured multi-omic database for atherosclerosis research, enabling broader access and utilisation within the scientific community.