Objective To study the prediction of pre-eclampsia in advanced age pregnant women by using of uterine artery Doppler combined with serum sflt-1,PlGF and PAPP-A. Method The prospective collective data study was conducted at antenatal care clinic Thammasat University Hospital. The pregnant women with age above 35 years old with gestational age between 18-24 weeks were recruited. The clinical risk factors were recorded. Uterine artery Doppler was performed at the same time with measurement of serum markers. The occurrence of pre-eclampsia and obstetrics outcomes were followed and recorded. All data was analyzed. Results The total enrolled pregnant women were 296. Only 276 pregnant women have complete information to analyze. 5.43 percent (15 pregnant women) had pre-eclampsia while 94.57 percent (261 pregnant women) had no pre-eclamptic symptoms. The baseline characteristics of both groups including age, body weight, body mass index, parity and history risk of pre-eclampsia were not statistically significant different. In pre-eclamptic group has higher percentage of abnormal uterine artery Doppler compared to non pre-eclamptic group (26.67%, 4/15 vs 16.48%, 46/261) but no significant different (p= 0.31). The ratio of sflt-1/PlGF in pre-eclamptic group were higher than non pre-eclamptic group ( 8.60 +4.79 vs 8.09 + 5.24) but no statistically significant different (p= 0.71). MoM( Median of mean ) of PAPP-A in pre-eclamptic group was less than non pre-eclamptic group but there is also no statistically significant. The logistic model was generated to predict the risk ratio of pre-eclampsia. The abnormal uterine artery Doppler has risk ratio (RR) 1.78, while the ratio of sflt-1/PlGF above 14 has RR 2.54. The MoM of PAPP-A less than 0.5 has RR 2.5 , respectively. Combination of these factors has prediction value for prediction 64.62%. Conclusion The combination of these factors could not be used to predict the occurrence of preelcampsia in advance age pregnant women . However, the incidence of preeclampsia in our study was lower than expectation , the larger sample size might be needed to verify this benefit.