Abstract The paper presents a new relaxation for hybrid planning with continuous numeric and propositional state variables based on subgoaling, generalising the subgoaling principle underlying the hmax and hadd heuristics to such problems. Our relaxation improves on existing interval-based relaxations b taking into account some negative interactions between effects when achieving a subgoal, resulting in better estimate We show conditions on the planning model ensuring that this new relaxation leads to tractable, and, for the hmax version admissible, heuristics. The new relaxation can be combined with the interval-based relaxation, to derive heuristics app cable to general numeric planning, while still providing mor informed estimates for the subgoals that meet these conditions. Experiments show the effectiveness of its inadmissible and admissible version on satisficing and optimal numeri planning, respectively. As far as we know, this is the first missible heuristic enabling cost-optimal numeric planning.