An important goal of growth monitoring is to identify genetic disorders, diseases or other conditions that manifest themselves through an abnormal growth. The two main conditions that can be detected by height monitoring are Turner’s syndrome and growth hormone deficiency. Conditions or risk factors that can be detected by monitoring weight or body mass index include hypernatremic dehydration, celiac disease, cystic fibrosis and obesity. Monitoring infant head growth can be used to detect macrocephaly, developmental disorder and ill health in childhood. This paper describes statistical methods to obtain evidence-based referral criteria in growth monitoring. The referral criteria that we discuss are based on either anthropometric measurement(s) at a fixed age using (1) a Centile or a Standard Deviation Score, (2) a Standard Deviation corrected for parental height, (3) a Likelihood Ratio Statistic and (4) an ellipse, or on multiple measurements over time using (5) a growth rate and (6) a growth curve model. We review the potential uses of these methods, and outline their strengths and limitations.