Objective: This study aimed to discover the prevalence of infant mortality and to assess how different factors influence infant mortality in 24 developing countries by utilizing the latest DHS data. Methods: This study used a mixed-method design to assemble cross-sectional studies to integrate data from 24 other countries due to a widening perspective of infant mortality. Most recent available DHS data of 24 different developing countries from the year 2013 to 2019 was used to conduct the study. Descriptive analysis, binary logistic regression model, random-effect meta-analysis, and forest plot have been used for the final analyses. Results: Binary logistic regression model revealed for Bangladesh that, higher education level of fathers (OR: 0.344, 95% CI: 0.147; 0.807), being 2nd born or above order infant (OR: 0.362, 95% CI: 0.248, 0.527), taking ANC (OR: 0.271, 95% CI: 0.192; 0.382 for 1-4 visits), taking PNC (OR: 0.303, 95% CI: 0.216; 0.425) were statistically significant determinants of lowering infant death. While carrying multiple fetus (OR: 6.634, 95% CI: 3.247; 13.555) was exposed as a risk factor of infant mortality. Most significant factors influencing infant mortality for all 24 developing countries were number of fetus (OR: 0.193, 95% CI: 0.176; 0.213), taking ANC (OR: 0.356, 95% CI: 0.311; 0.407) and taking PNC (OR: 0.302, 95% CI: 0.243; 0.375). Conclusion In this study, the number of the fetus, taking ANC and PNC, was the most significant factor affecting the risk of infant mortality in developing countries. So, anticipation and control projects ought to be taken in the field in regard to these hazard factors.