We give a fully polynomial randomized approximation scheme for all-terminal unreliability in explicitly represented undirected hypergraphs of arbitrary rank. The algorithm estimates the probability that independent hyperedge failures disconnect the hypergraph, allowing a different rational failure probability for every edge. For a common failure probability, this improves the quasi-polynomial approximation schemes of Cen, Li, and Panigrahi to polynomial time and answers the polynomial-time approximation question reiterated in their subsequent work on graphs. The construction turns their representative-survival bound into an importance sampler whose relative second moment is bounded solely in terms of the number of vertices. We protect one randomly chosen representative pair during contraction, correct the path likelihood, and divide by the number of pairs surviving at the end. The resulting unbiased estimator has relative second moment at most $\binom n2$, even when unreliability is exponentially small. A minimum-cut normalization makes this estimator implementable with polynomially bounded precision: the residual likelihood becomes a survival probability in an auxiliary absorbing process, which admits rational discretization with a fixed random-bit budget. Logarithmic rate rounding and an exact weighted minimum cut extend the construction to unequal rational failure probabilities. The algorithm's worst-case running time and random-bit usage are polynomial in the input length, the inverse relative error, and $\log(1/δ)$ for confidence $1-δ$.

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