We introduce a new class of backward stochastic differential equations in which the T-terminal value YT of the solution (Y,Z) is not fixed as a random variable, but only satisfies a weak constraint of the form E[.(YT)].m, for some (possibly random) nondecreasing map . and some threshold m.We name them BSDEs with weak terminal condition and obtain a representation of the minimal time t-values Yt such that (Y,Z) is a supersolution of the BSDE with weak terminal condition.It provides a non-Markovian BSDE formulation of the PDE characterization obtained for Markovian stochastic target problems under controlled loss in Bouchard, Elie and Touzi [SIAM J. Control Optim.48 (2009/10) 3123.3150].We then study the main properties of this minimal value. In particular, we analyze its continuity and convexity with respect to the m-parameter appearing in the weak terminal condition, and show how it can be related to a dual optimal control problem in Meyer form.These last properties generalize to a non-Markovian framework previous results on quantile hedging and hedging under loss constraints obtained in Föllmer and Leukert [Finance Stoch.3 (1999) 251.273; Finance Stoch.4 (2000) 117.146], and in Bouchard, Elie and Touzi (2009/10)