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Abstract Neonatal mortality is the death of a live-born infant within the first 28 completed days of life. Neonatal mortality remains a major public health concern in most African countries, with the Sub-Saharan region being the highest contributor at 27 deaths per 1000 live births, accounting for 43% of the total number of deaths. Zambia still fares poorly in terms of neonatal mortality, ranking 162 out of 195 countries globally. The study aimed to investigate the spatial patterns and predictors of neonatal mortality in rural Zambia. This study utilized the national-level data from the Zambia Demographic and Health Survey (ZDHS) program, utilizing the survey dataset from 2018. Statistical analyses were conducted using the Rao – Scott Chi-square test to assess associations between dependent and independent variables. Additionally, a multilevel mixed effect logistic regression model was used to examine predictors of neonatal mortality. Geospatial patterns of neonatal mortality across Zambia’s ten provinces were investigated using Quantum Geographical Information System (QGIS) version 3.34.1 to generate a univariate choropleth map. Data analysis was performed using Stata version 14.2. The study findings indicate a higher mortality rate among HIV-infected mothers aged 45 to 49 (100%) compared to 95.21% among non-HIV-infected mothers. Neonatal mortality was notably elevated among neonates born to mothers with no education (40.78%) and those with HIV infection (54.56%). Employment status also influenced mortality rates, with employed non-HIV-infected mothers showing 36.35% mortality compared to 49.39% among unemployed HIV-infected mothers. Higher birth weights, particularly 4000 grams or higher, were associated with increased mortality for both HIV-infected (81.15%) and non-infected (21.00%) mothers. Multilevel logistic regression identified predictors of mortality, including maternal age (40 to 44 years), neonate’s sex (female), and maternal HIV status. Geospatial analysis revealed Eastern and North-Western provinces as hotspots for neonatal mortality among HIV-infected mothers, while Muchinga was a hotspot for non-HIV-infected mothers. This study examined neonatal mortality among HIV-infected and non-infected mothers in rural Zambia, uncovering predictors such as maternal age, neonate sex, birthweight, maternal HIV status, and community desired number of children. Regional variations in mortality underscore the necessity for targeted interventions. Strengthening healthcare infrastructure, community outreach, healthcare worker training, maternal education, and addressing regional differences are crucial for improving maternal and child health and meeting Sustainable Development Goals targets.