Clinical trials in child psychiatry research have increased in complexity. Several factors have contributed to this change, including the need to compare multiple therapies, to re-create clinically relevant situations in research, to standardize treatment approaches, to account for the impact of comorbidity, to respond to the needs of individual patients, and to optimize treatment accordingly. To preserve the clinical and internal validity of the experimental interventions vis-à-vis their increasing complexity, researchers have started developing treatment algorithms. These deductive systems for handling data allow us to standardize and incorporate clinical judgment into study designs through the adoption of a stepwise decision making process. Treatment algorithms are different from treatment guidelines. Guidelines are general recommendations that apply to groups of patients with certain characteristics; they are not fully detailed and are created with the expectation that clinical judgment will be applied in individual cases. Algorithms are patient specific, are intended to capture all the relevant details of the clinical situation, and require minimal clinical judgment for their clinical application; they are designed to minimize the role of clinical judgment in research protocols. The entire multistep algorithm is tested in a clinical trial, not the single steps that constitute the algorithm, so proving the efficacy of an algorithm cannot replace a controlled assessment of the individual treatments embedded in the algorithm. Some characteristics, properties, and limitations of algorithms in child psychiatry and psychopharmacology research are presented along with two examples of algorithms currently used in child and adolescent psychopharmacology. Although treatment algorithms seldom have been used in pediatric psychiatry and psychopharmacology, there are indications that their use will increase in the near future and will allow the standardized introduction of clinical judgment into research design.