<p>What pay can a worker reasonably expect when facing uncertainty about their own productivity and that of their co-workers? We address this question through three complementary approaches. First, we propose an axiomatic framework that extends the neoclassical model of the firm to account for imperfect information. A new set of axioms, generalizing classical fairness principles, uniquely determines a fair expected payoff—though this allocation need not be stable. Second, we introduce the probabilistic core, a new solution concept that identifies stable allocations under uncertainty, even when they deviate from fairness. We reconcile fairness and stability by identifying a new class of technologies—<i>quasimodular technologies</i>—for which the fair allocation lies in the core, making it both fair and stable. Third, we study a strategic environment where uncertainty arises endogenously from costly effort. When pay follows the fair scheme, we derive conditions for the existence, uniqueness, and Pareto efficiency of a Nash equilibrium, with each equilibrium determining an expected pay. Although motivated by labor markets, the framework has broader applicability. We extend it to asset valuation under volatility and interdependence, and to Cournot oligopoly, where it reproduces the classical equilibrium—showing that fairness-based pay expectations can align with profit-maximizing behavior.</p>