This study proposes a simple algorithm for grading histological activity in chronic hepatitis C, which is as accurate as a statistical approach. The algorithm, developed by a panel of 10 pathologists, uses piecemeal necrosis and lobular necrosis to determine activity scores. The algorithm was validated against a reference activity, which was determined by the same pathologists. The concordance between the algorithm and reference activity was substantial (κ = 0.75), with 84% of cases correctly graded. A statistical model was also developed using stepwise discriminant analysis, which identified piecemeal necrosis, lobular necrosis, and portal inflammation as key features. The concordance between the statistical model and reference activity was also substantial (κ = 0.73), with 83% of cases correctly graded. Both methods showed good agreement, indicating that the algorithm is a reliable tool for grading histological activity in chronic hepatitis C. The algorithm is simple, reproducible, and can be applied to a large number of biopsies. It is based on two reproducible features: piecemeal necrosis and lobular necrosis. The algorithm is used in the METAVIR scoring system, which is widely used in France for evaluating chronic hepatitis C. The system includes a two-letter and two-number coding system for activity and fibrosis. The proposed algorithm provides an easy means of scoring the activity of chronic hepatitis C.This study proposes a simple algorithm for grading histological activity in chronic hepatitis C, which is as accurate as a statistical approach. The algorithm, developed by a panel of 10 pathologists, uses piecemeal necrosis and lobular necrosis to determine activity scores. The algorithm was validated against a reference activity, which was determined by the same pathologists. The concordance between the algorithm and reference activity was substantial (κ = 0.75), with 84% of cases correctly graded. A statistical model was also developed using stepwise discriminant analysis, which identified piecemeal necrosis, lobular necrosis, and portal inflammation as key features. The concordance between the statistical model and reference activity was also substantial (κ = 0.73), with 83% of cases correctly graded. Both methods showed good agreement, indicating that the algorithm is a reliable tool for grading histological activity in chronic hepatitis C. The algorithm is simple, reproducible, and can be applied to a large number of biopsies. It is based on two reproducible features: piecemeal necrosis and lobular necrosis. The algorithm is used in the METAVIR scoring system, which is widely used in France for evaluating chronic hepatitis C. The system includes a two-letter and two-number coding system for activity and fibrosis. The proposed algorithm provides an easy means of scoring the activity of chronic hepatitis C.