Background: Coronavirus disease 2019 (COVID-19) has costed the lives of more than 2 million people during the first wave of the pandemic with the number of fatalities varying among different countries. Thus, we aimed to assess the associations of specific demographic, clinical and political variables with COVID-19 related fatalities in various countries, during the first three months of the pandemic. Methods: We analyzed publicly available data from 192 regions (114 countries) and built a log-linear regression model with random intercepts in order to identify predictors of COVID-19 fatalities during the first three months of the pandemic. We used country-level data including total population, the percentage of people aged 65 and above, number of ICU beds per 100,000 people, geographical latitude and number of days from the first confirmed COVD-19 case to establishment of specific preventive control measures as explanatory variables of our statistical model. Results: In our multivariate statistical model, one unit increases in the total population (in 10,000,000 units), percentage of population aged 65 and above and the number of days from the first confirmed COVID-19 case to the imposition of preventive measures, were related to 3.8% (95% CI: 0.8% to 6.9%), 7.1% (95% CI: 0.9% to 13.6%) and 1.8% (95% CI: 0.3% to 3.6%), respectively, higher number of COVID-19 related deaths. Conclusion: Our findings imply positives associations of total population, percentage of population aged 65 and above and number of days from the first confirmed COVID-19 case to the imposition of preventive measures with COVID-19 fatal cases, during the first three months of the pandemic. Future non-ecological studies are warranted to confirm our results.