Preterm birth is a global health problem. It is the leading cause of child and neonatal mortality globally including Kenya. Preterm birth is the birth occurring before 37 completed weeks of gestation. In Kenya, preterm birth is the leading cause of neonatal mortality as it contributes to 35% of deaths among the neonates while Kisumu County is among the county’s leading with child under-five mortality rate at 133 deaths per 1000 live births. The main objective of this study was to identify the clinical phenotypes associated with preterm birth in JOOTRH in Kisumu County. It was a cross sectional study based on women who had a preterm birth alive or stillbirth at JOORTH in Kisumu County. Purposive sampling technique was used to select 178 respondents who met the inclusion criteria. Interviewer administered questionnaire was used to collect both qualitative and quantitative data. Data was analyzed by computer software SPSS version 23; descriptive statistics was used together with inferential statistics (Chi-square and Fisher’s Exact test) to help in the identification of the statistical significance of any association between the variables. A p value of < 0.05 was used. Bivariate analysis was utilized to measure the strength of associations. Data presented by use of frequency tables and narrative description. Ethical clearance was sought from Kenyatta University Ethics and Review Committee, permit sought from NACOSTI, consent and assent from the respondents. Results showed that maternal age (p=0.011) to be statistical significant with preterm births. Clinical phenotypes based on maternal, fetal and placental conditions; preeclampsia/eclampsia (p=0.016), extrauterine infections which includes malaria, UTI and HIV (p=0.030), severe maternal conditions that includes DM, anaemia, cardiac disease, hypertension prior to pregnancy and TB (p=0.001), multiple gestations (p=0.013), fetal anomaly (0.048), IUGR (p=0.049), antepartum stillbirth (p=0.046) and APH/early bleeding that include placenta previa and placenta abruption (p=0.025) were all significantly associated with preterm births. On bivariate analysis between clinical phenotypes and preterm births, all except multiple gestation (p=0.416) and APH (p=0.660) remained statistically significant. All clinical phenotypes (maternal, fetal and placental conditions) were significantly associated with preterm births. All clinical phenotypes except multiple gestations and APH/early bleeding remained statistically significant after bivariate analysis. The study recommends the use of Barro’s classifications system of clinical phenotypes to phenotype all preterm births in JOOTRH. Early identification of maternal, fetal and placental conditions identified in this study to be associated with preterm births by adopting Barros’ phenotyping of preterm births as a strategy to help prevent the occurrence of PTBs and eventually reduce neonatal deaths and under-five mortality.