Introduction: In many parts of the developing world procurement of antenatal gestational age estimates is not possible, challenging provision of appropriate perinatal care. This study aimed to develop a model for postnatal gestational age estimation utilizing measures of the newborn hemoglobin levels and other metabolic analyte data derived from newborn blood spot samples. Methods: We conducted a retrospective cohort analysis of 159,215 infants born January 2012–December 2014 in Ontario, Canada. Multivariable linear and logistic regression analyses were used to evaluate the precision of developed models. Results: Models derived from a combination of hemoglobin ratios and birthweight were more precise at predicting gestational age (RMSE1·23 weeks) than models limited to birthweight (RMSE1·34). Models including birthweight, hemoglobin, TSH and 17-OHP levels were able to accurately estimate gestational age to ±2 weeks in 95·3% of the cohort and discriminate ≤34 versus >34 (c-statistic, 0·98). This model also performed well in small for gestational age infants (c-statistic, 0·998). Discussion: The development of a point-of-care mechanism to allow widespread implementation of postnatal gestational age prediction tools that make use of hemoglobin or non-mass spectromietry-derived metabolites could serve areas where antenatal gestational age dating is not routinely available.