Researchers have recently begun to use a behavioral economics framework to study the clinicalethical decisions made by practicing behavior analysts. Much of this work, however, has examined broad patterns as opposed to isolating the underlying behavioral processes. In this study, we sought to extend past research by studying how clinical-ethical decisions would be influenced by a parametric manipulation of the probability that each available option would be televisible or cause short-term harm to the client. Behavior analysts (n=15) were largely influenced only by the probability of short-term harm. In contrast, the control group (n=30) was influenced by the probability each choice was televisible and the probability of short-term harm. Further, across all choices, control group participants showed a higher tendency than behavior analysts to not allow the individual to engage in the harmful behavior. Quantitative models built using machine learning algorithms were able to predict ~75% of choices made by participants using only the independent variables manipulated in this study. At the individual level, a probability loss discounting framework seemed to account for the data; however, deviations from traditional probability loss discounting methods provide many areas for future research. In total, the present experiment highlights the potential behavioral processes involved in clinical-ethical choices, similarities between individual (moral) and group-level (ethical) responding, and areas where practicing behavior analysts may have preferences that differ from their clients or their clients' caregivers.