Probabilistic rules are at the core of probabilistic structured argumentation. With a language unmapped: inline-formula unmapped: math unmapped: mi L, probabilistic rules describe conditional probabilities unmapped: inline-formula unmapped: math unmapped: mo Prunmapped: mo (unmapped: msub unmapped: mrow unmapped: mi σunmapped: mrow unmapped: mn 0unmapped: mo |unmapped: msub unmapped: mrow unmapped: mi σunmapped: mrow unmapped: mn 1unmapped: mo ,unmapped: mo …unmapped: mo ,unmapped: msub unmapped: mrow unmapped: mi σunmapped: mrow unmapped: mi kunmapped: mo ) of deducing some sentences unmapped: inline-formula unmapped: math unmapped: msub unmapped: mrow unmapped: mi σunmapped: mrow unmapped: mn 0unmapped: mo ∈unmapped: mi L from others unmapped: inline-formula unmapped: math unmapped: msub unmapped: mrow unmapped: mi σunmapped: mrow unmapped: mn 1unmapped: mo ,unmapped: mo …unmapped: mo ,unmapped: msub unmapped: mrow unmapped: mi σunmapped: mrow unmapped: mi kunmapped: mo ∈unmapped: mi L by means of prescribing rules unmapped: inline-formula unmapped: math unmapped: msub unmapped: mrow unmapped: mi σunmapped: mrow unmapped: mn 0unmapped: mo ←unmapped: msub unmapped: mrow unmapped: mi σunmapped: mrow unmapped: mn 1unmapped: mo ,unmapped: mo …unmapped: mo ,unmapped: msub unmapped: mrow unmapped: mi σunmapped: mrow unmapped: mi k with head unmapped: inline-formula unmapped: math unmapped: msub unmapped: mrow unmapped: mi σunmapped: mrow unmapped: mn 0 and body unmapped: inline-formula unmapped: math unmapped: msub unmapped: mrow unmapped: mi σunmapped: mrow unmapped: mn 1unmapped: mo ,unmapped: mo …unmapped: mo ,unmapped: msub unmapped: mrow unmapped: mi σunmapped: mrow unmapped: mi k. In Probabilistic Assumption-based Argumentation (PABA), a few constraints are imposed on the form of probabilistic rules. Namely, (1) probabilistic rules in a PABA framework must be acyclic, and (2) if two rules have the same head, then the body of one rule must be the subset of the other. In this work, we show that both constraints can be relaxed by introducing the concept of Rule Probabilistic Satisfiability (Rule-PSAT) and solving the underlying joint probability distribution on all sentences in unmapped: inline-formula unmapped: math unmapped: mi L. A linear programming approach is presented for solving Rule-PSAT and computing sentence probabilities from joint probability distributions.