Brief experimental analysis (BEA) can be used to specify intervention characteristics that produce positive learning gains for individual students. A key challenge to the use of BEA for intervention planning is the identification of performance indicators (including topography of the skill, measurement characteristics, and decision criteria) that meaningfully relate to longer term success in the learning environment. This study investigates the utility of various curriculum-based assessment and measurement estimates of mathematics performance for predicting functional outcomes (i.e., retention of learned skills over time and faster learning of related content in the future). All children in grades 2-5 at the participating school participated in protocol-based computational fluency-building intervention 4 days per week for an entire school year. Specific criteria were applied each week to systematically increase intervention difficulty classwide according to a pre-established sequence of computational skill objectives. Three measurements were routinely obtained. Each week children completed a timed probe of the skill for which intervention was currently occurring and a timed probe of previously mastered skills from the sequence of computational skill objectives. Each month, all children completed a timed probe of mathematics skills representing computational skills that students were expected to master by year's end at each grade level. At all grade levels, learning a skill that appeared early in the hierarchy or sequence of skills related positively to learning of future related and more complex computational skills. Fluency criteria were specified that predicted retention of the skill over several months.