________________________________________ *Corresponding author: Email: jdioggban@cktutas.edu.gh, dominicatiah83@gmail.com; Asian J. Prob. Stat., vol. 22, no. 4, pp. 41-48, 2023 Asian Journal of Probability and Statistics Volume 22, Issue 4, Page 41-48, 2023; Article no.AJPAS.98634 ISSN: 2582-0230 _______________________________________________________________________________________________________________________________________ Modeling Maternal Factors for Predicting Birth Outcomes in Ghana Atiah Dominic Baazand a , Jakperik Dioggban b* and Engmann Gideon Mensah b a Department of Statistics, C. K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana. b Department of Biometry, C. K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana. Authors’ contributions This work was carried out in collaboration among all authors. All authors read and approved the final manuscript. Article Information DOI: 10.9734/AJPAS/2023/v22i4491 Open Peer Review History: This journal follows the Advanced Open Peer Review policy. Identity of the Reviewers, Editor(s) and additional Reviewers, peer review comments, different versions of the manuscript, comments of the editors, etc are available here: https://www.sdiarticle5.com/review-history/98634 Received: 22/03/2023 Accepted: 24/05/2023 Published: 01/06/2023 __________________________________________________________________________________ Abstract This study was conducted to identify the various maternal and neonatal factors that influence birth outcomes. Maternal and neonatal factors are key determinants of birth outcomes and the health of a newborn baby is very crucial in the first six months of the baby’s life. Neonatal mortality and low birth weight are worrying problems for stakeholders in the health sector. Logistic regression and multilevel regression were used to study various factors that influence birth outcomes. Secondary data was therefore collected from the War Memorial Hospital, Navrongo for the purpose of the study. The results show that weight, birth weight, gestation weeks and hemoglobin were observed as significant risk factors for birth outcomes whilst age, weight, hemoglobin, mode of delivery and gestation weeks were identified as significant factors that influence birth weight. The study identified weight, hemoglobin, birth weight, gestation weeks and age as factors that influence birth outcomes in the Kassena-Nankana Municipality. Keywords: Maternal factors; birth outcome; birth weight; binary logistic; mixed effects model. Original Research Article