This case study explores and contrasts multiple regression techniques to forecast COVID-19 cases and deaths using past data trends. COVID-19, an unparalleled global crisis, has redefined the dimensions of public health, socioeconomics, and geopolitics, putting to test the resilience and flexibility of global systems. As the novel coronavirus rapidly traversed international boundaries, countries were thrust into an urgent battle to decode and stem its persistent spread. Facing escalating hospitalizations, economic downturns, and strained healthcare systems, the imperative to anticipate the trajectory of the pandemic grew. Within this context, predictive modeling, particularly the capacity to project imminent cases and fatalities, stands out as a crucial element in strategic decision-making. This methodology aids governments in optimizing resource distribution, devising policies, and preparing communities for potential waves of infections.