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In diseases caused by a deleterious gene mutation, knowledge of age-specific cumulative risks is necessary for medical management of mutation carriers. When pedigrees are ascertained through at least one affected individual, ascertainment bias can be corrected by using a parametric method: the Proband’s phenotype Exclusion Likelihood or PEL. This method, using a survival analysis approach based on the Weibull model, has been shown to be unbiased when family samples are simulated from aWeibull distribution. This paper proposes a nonparametric method for penetrance function estimation that corrects for ascertainment on at least one affected: the Index Discarding EuclideAn Likelihood or IDEAL. IDEAL is compared with PEL, using family samples simulated from a Weibull distribution and under alternative models. We show that, under Weibull assumption and asymptotic conditions, IDEAL provides unbiased estimates and thus, competed with PEL. When this assumption fails, PEL is biased while IDEAL remains unbiased. Key Words: Risk estimation, ascertainment bias, nonparametric method