Soil erosion, particularly in data-scarce areas, is among the significant challenges to sustainable land and watershed management. This study develops an empirical equation to estimate the rainfall erosivity factor (R-factor), a key parameter in soil loss models. The specific objectives were to evaluate existing R-factor equations representing similar climatic regions and to propose an applicable equation for the study site. The rainfall data from Porac, Pampanga, Philippines, and surrounding areas were analyzed using the inverse distance weighted (IDW) method. Eight global R-factor equations were tested for applicability, and a new equation obtained was derived incorporating locally scaled variables. Results show that August accounted for the highest value of R-factor, equal to 371.3 MJ/ha<middle dot>mm/h, while February received the lowest, ranging from 0.096 to 2.901 MJ/ha<middle dot>mm/h. Thus, the results suggest that the derived equation aligns with existing R-factor formulas but shows discrepancies with certain formulas designed for highly specific conditions. These findings provide a well-grounded framework for soil loss estimation where rainfall data might be scarce, thus supporting improved soil conservation strategies due to better predictions of soil erosion, particularly in tropical and developing regions exposed to severe erosion risks.