Using conventional statistical analysis and multiple regression analysis, we investigated the viral and host factors that influence the response to recombinant interferon-alpha 2a therapy in patients with chronic hepatitis C. A total of 36 patients was randomly assigned to three administration schedules, 12 patients in each. Response to treatment was set as the criterion variable. Four variables were statistically significant in the conventional method in predicting a good therapeutic outcome: HCV genotype III and IV, lower histology activity index (HAI) score for liver, higher total dose of interferon administration, and lower serum HCV RNA concentration. In multiple regression analysis, a combination of the above four variables resulted in a higher multiple correlation coefficient (R = 0.84, P < 0.0001) using a stepwise method. Of those four, HCV genotype had the highest absolute value of standard partial regression coefficient (0.51). The HCV RNA concentration was correlated with HCV genotype and HAI score, whereas HCV genotype and HAI score showed no correlation. Thus, HCV RNA concentration was not statistically significant in multiple regression analysis. These findings indicate that HCV genotype, HAI score, and schedule of administration can be important predictors of the response to interferon therapy.