Understanding the relationship between hillslope soil loss with ephemeral gully and rainfall regime is important for soil loss prediction and erosion control. Based on 12-year field observation data, this paper quantified the rainfall regime impacts on soil loss at loessial hillslope with ephemeral gully. According to three rainfall parameters including precipitation(P), rainfall duration(t), and maximum 30-minute rainfall intensity(I_(30)), 115 rainfall events were classified by using K-mean clustering method and Discriminant Analysis. The results showed that 115 rainfall events could be divided into three rainfall regimes. Rainfall Regime 1(RR1) had large I_(30) values with low precipitation and short duration, while the three rainfall parameters of Rainfall Regime 3(RR3) were inversely different compared with those of RR1; for Rainfall Regime 2(RR2), the precipitation, duration and I_(30) values were all between those of RR1 and RR3. Compared with RR2 and RR3, RR1 was the dominant rainfall regime for causing soil loss at the loessial hillslope with ephemeral gully, especially for causing extreme soil loss events. PI30(Product of P and I_(30)) was selected as the key index of rainfall characteristics to fit soil loss equations. Two sets oflinear regression equations between soil loss and PI_(30) with and without rainfall regime classification were fitted. Compared with the equation without rainfall regime classification, the cross validation results of the equations with rainfall regime classification was satisfactory. These results indicated that rainfall regime classification could not only depict rainfall characteristics precisely, but also improve soil loss equation prediction accuracy at loessial hillslope with ephemeral gully. Understanding the relationship between hillslope soil loss with ephemeral gully and rainfall regime is important for soil loss prediction and erosion control. Based on 12-year field observation data, this paper quantified the rainfall regime impacts on soil loss at loessial hillslope with ephemeral gully. to rainfall parameters were precipitation (P), rainfall duration (t), and maximum 30-minute rainfall intensity (I_ (30)), 115 rainfall events were classified by using K-mean clustering method and Discriminant Analysis. The results said that Rainfall Regime 1 (RR1) had large I_ (30) values ​​with low precipitation and short duration, while the three rainfall parameters of Rainfall Regime 3 (RR3) were inversely different different with those of RR1; for Rainfall Regime 2 (RR2), the precipitation, duration and I_ (30) values ​​were all among those RR1 and RR3. Compared with RR2 and RR3, RR1 was the dominant r ainfall regime for causing soil loss at the loessial hillslope with ephemeral gully, especially for causing extreme soil loss events. PI30 (Product of P and I_ (30)) was selected as the key index of rainfall characteristics to fit soil loss equations. Compared with the without rainfall regime classification were fitted. with the result of that rainfall regime classification was satisfactory. These results indicate that rainfall regime classification were fitted. could not only depict rainfall characteristics precisely, but also improve soil loss equation prediction accuracy at loessial hillslope with ephemeral gully.