Birthweight (BW) is an important predictor of newborn morbidity and mortality. In Africa, infant mortality is very high mainly due to low birthweight (LBW). Most deliveries occur at home where scales are not always available. The aim of this study was to find a simple formula to predict birthweight using anthropometric measurements. In 1000 singleton Sudanese newborns, anthropometric measurements were taken within 24 hours of birth. Multiple regression analysis with backward selection was used to analyze data. The mean (standard deviation) of BW was 3131.7 (538.9) g and that of gestational age was 39.1 (1.8) weeks. All anthropometric parameters were strongly correlated with BW ( P < 0.001). The highest correlations were obtained with chest (CC), midthigh (MT), and head circumferences (HC). Using these three parameters, a simple formula was obtained to predict BW as follows: BW(g) = 97*CC + 74*MT + 85*HC - 4000 with a standard error of 285 g. For birthweights < 2000 g, specificity is near 100% and the sensitivity is > 80%. Applying a cutoff point of 2500 g, all infants (100%) with a birthweight < 2000 g are correctly identified. Our model by allowing for actual measurement of BW will enable the health worker in developing countries to select appropriate LBW infants for referral to an equipped health facility.