This paper proposes a biometric personal authentication based on the pressure distribution while one step walking. We extract one step from a walk on a mat type load distribution sensor and use it to personal authentication. With this method, features which are based on weight movement and foot shape during walking are calculated, then a classifier is developed on the basis of fuzzy inference. We employed 30 volunteers. All volunteers are ranged from 20 to 85 years old. For each volunteer, we took walk data six times. Then, we evaluated this method by five training data and one test data. We obtained 6.1% EER (Equal Error Rate) and 13.9% FRR (False Rejection Rate) in verification (1:1 collation) and identification (1:N collation), respectively.