Tirzepatide's effectiveness varies dramatically between individuals based on clinical factors like diabetes duration, β-cell function, baseline HbA1c, and patient demographics, plus genetic variants in GLP-1 receptor, GIP receptor, and obesity-related genes like MC4R and FTO. Molecular biomarkers including branched-chain amino acids, adiponectin-to-leptin ratio, and inflammatory markers like IL-6 and CRP correlate with metabolic response patterns. This multidimensional variability represents a significant advancement in understanding precision diabetes medicine. Unlike single-target therapies, tirzepatide's dual GLP-1/GIP mechanism creates complex response patterns that traditional one-size-fits-all dosing cannot optimize. The identification of specific genetic variants and biomarker profiles could enable clinicians to predict which patients will achieve superior glycemic control, weight loss, or organ protection before initiating therapy. However, most genetic associations derive from GLP-1 studies rather than tirzepatide-specific research, limiting immediate clinical application. The integration of clinical characteristics with genetic testing and biomarker profiling could transform diabetes care from reactive dose adjustments to proactive precision prescribing, potentially improving outcomes while reducing treatment failures and healthcare costs.