Background. Translational research is a complex cumulative process that takes time. However, the operating environment for cancer centers engaged in translational research is now financially insecure. Centers are challenged to improve results and reduce time from discovery to practice innovations. Performance assessment can identify improvement areas that will help reduce translational delays. Currently, no standard method exists to identify models for use in performance assessment. This study aimed to critically appraise translational research models for suitability in performance assessment of cancer centers. Methods. We conducted a systematic review to identify models and developed a set of criteria based on scientometrics, complex adaptive systems, research and development processes, and strategic evaluation. Models were assessed for linkage between research and care components, new knowledge, systems integration, performance assessment, and review of other models. Results. Twelve models were identified; six described phases/components for translational research in different blocks (T models) and six described the process of translational research (process models). Both models view translational research as an accumulation of new knowledge. However, process models more clearly address systems integration, link research and care components, and were developed for evaluating and improving the performance of translational research. T models are more likely to review other models. Conclusion. Process models seem to be more suitable for performance assessment of cancer centers than T models. The most suitable process models (the Process Marker Model and Lean and Six Sigma applications) must be thoroughly tested in practice.