MatchPRO
While manual matching by veteran staff resulted in a 29.41% early match endings, MentorPRO’s precision algorithms reduced early closures to a mere 10.87%, effectively tripling the reliability of every connection made.
Why a Scientific Approach to Matching Matters
Matching mentors and mentees sounds straightforward, but the research on what actually predicts a strong, lasting mentoring relationship is more nuanced than most programs realize. Match on the wrong variables and you get pairs that close early, disengage, or never develop the trust needed to produce real growth. Match on the right ones and you get relationships that go the distance.
Most mentoring platforms offer matching as an administrative convenience. MatchPRO treats it as the most consequential decision in the entire mentoring process, because the evidence says it is. Our pairings are 3x more likely to endure than those assigned manually.
Built by the World’s Leading Expert on Mentoring Matching
The MatchPRO matching algorithm was developed by Jean Rhodes, Professor of Psychology at the University of Massachusetts Boston and Director of the Center for Evidence-Based Mentoring. Over the course of her career, Dr. Rhodes has published more than 200 peer-reviewed studies on mentoring relationships and programs. That body of work deeply informs the algorithm.
No other mentoring platform was built by someone who has the expertise to know what makes a good match.
What the Real-World Data Shows
“Among pairs matched through MentorPRO, only 10.87 percent ended early. Among pairs assigned manually by experienced staff, 29.41 percent closed before completion, nearly three times the rate.”
Programs using MatchPRO have seen stronger, more persistent matches. Our partnership with Zing Programme offered an opportunity to examine this question directly. Across a sample of 333 mentoring matches, we used random assignment to compare early match closure rates between mentors whose matches were made using MatchPRO (n = 133) and those whose matches were made manually by program staff (n = 200). The results were striking. MatchPRO matches experienced an early closure rate of only 10.87%, compared to 29.41% in the manually matched condition, a difference of more than 18 percentage points. See the data here.
For any organization investing time, staff resources, and relationship capital in each pair, that is a significant difference. Research consistently shows that premature match closures can be harmful to mentees, particularly young people from marginalized backgrounds (Rhodes, 2020). Matches that stay together produce better outcomes.
The research is clear. MatchPRO matched pairs stay together longer and perform better.
Algorithmic Matching vs. Manual Assignment
| Criteria |
Recommended
MentorPRO Algorithm |
Traditional
Manual Matching |
|---|---|---|
| Variables considered | Program preferences + evidence-based variables | Varies by coordinator experience |
| Customization | Fully customizable, consistent process | Subject to human variability |
| Scalability | Scales to any program size | Labor-intensive at scale |
| Premature termination
Independent data |
10.89% | 29.41% |
| Relationship quality score
Zing data |
Higher | Lower |
| Evidence base | Practitioner judgement + research expertise | Practitioner judgment |
| Customizable | Yes | Yes |
Programs that rely on manual matching are not doing something wrong. Experienced coordinators bring real judgment and contextual knowledge to the process, and they always have the final say on any suggested pairing. But manual matching is limited by time, cognitive bandwidth, and the number of variables any one person can weigh at once. An algorithm built on decades of research does not get tired, does not carry unconscious preferences, and does not run out of capacity when a program scales.
How MatchPRO Matching Works
The MatchPRO matching process is customizable, transparent, and grounded in more than 30 years of research. Programs work with our team of experts to identify the variables that matter most for their specific population and context. No two programs are identical, and our system is built to reflect that.
The process follows four steps:
Program managers identify their matching variables based on their preferences and our research-backed library, with the option to add variables specific to their program.
MentorPRO generates a customized intake form linked directly to the platform.
Mentors and mentees complete the form, and program managers can designate a point person to review submissions.
Program managers review the algorithm-generated match list, confirm pairings, and grant platform access. Pairs can be re-matched in future program cycles as needed.
What is mentoring matching?
Mentoring matching is the process of pairing mentors and mentees based on shared characteristics, goals, and compatibility factors. When done well, it produces more stable relationships and better outcomes for both parties.
Is algorithmic matching better than manual matching?
Data from Zing Programme found that MentorPRO-matched pairs had an early closure rate of 10.87 percent compared to 29.41 percent for manually assigned pairs, with higher relationship quality scores as well. Manual matching draws on valuable practitioner judgment but is limited by time and cognitive capacity in ways a research-driven algorithm is not.
What variables does MentorPRO use for matching?
MentorPRO draws on more than 15 research-driven variables, including demographics, language fluency, goals, interests, availability, and program-specific criteria, with particular emphasis placed on mentee preferences. All variables are customizable in consultation with our team.
Can programs of any size use MentorPRO matching?
Yes. MentorPRO’s algorithm scales from small cohorts to programs with hundreds of pairs, maintaining consistency across every match without increasing staff workload.
Is MentorPRO matching available for international programs?
Yes. Zing Programme in Spain is one example of an international partner using MentorPRO’s matching system with strong results across a culturally diverse population.
What are the peer-reviewed articles supporting MentorPRO’s matching?
Ramadurai, R., Deng, Y., Werntz, A., Yowell, C., and Rhodes, J. E. (2025). Mentor-mentee similarity in college peer mentoring: Untangling conflicting results. Studies in Higher Education. https://doi.org/10.1080/03075079.2025.2572504
Raposa, E. B., Ben-Eliyahu, A., Olsho, L., and Rhodes, J. (2019). Birds of a feather: Is matching based on shared interests and characteristics associated with longer youth mentoring relationships? Journal of Community Psychology, 47(2), 385-397. https://doi.org/10.1002/jcop.22127
Spencer, R., Gowdy, G., Drew, A. L., and Rhodes, J. E. (2018). “Who knows me the best and can encourage me the most?”: Matching and early relationship development in youth-initiated mentoring relationships. Journal of Adolescent Research. https://doi.org/10.1177/0743558417705491
Kupersmidt, J., Stump, K., Stelter, R., and Rhodes, J. (2017). Predictors of premature match closure in youth mentoring relationships. American Journal of Community Psychology. https://doi.org/10.1002/ajcp.12153
Kupersmidt, J., Stump, K., Stelter, R., and Rhodes, J. (2017). Mentoring program practices as predictors of match longevity. Journal of Community Psychology. https://doi.org/10.1002/jcop.21883
Rhodes, J., Schwartz, S., Willis, M. M., and Wu, M. V. (2017). Validating a mentoring relationship quality scale: Does match strength predict match length? Youth and Society, 49(4), 415-437. https://doi.org/10.1177/0044118X14531603
Grossman, J. B., Chan, C. S., Schwartz, S. E. O., and Rhodes, J. E. (2012). The test of time in school-based mentoring: The role of relationship duration and re-matching on academic outcomes. American Journal of Community Psychology. https://doi.org/10.1007/s10464-011-9435-0
Kanchewa, S., Rhodes, J. E., Schwartz, S. E. O., and Olsho, L. (2014). The influence of same- versus cross-gender matching in formal youth mentoring programs. Applied Developmental Science. https://doi.org/10.1080/10888691.2014.927358
Rhodes, J. E., Reddy, R., and Rappaport, N. (2005). Promoting successful youth mentoring relationships: A preliminary screening questionnaire. Journal of Primary Prevention, 26(2), 147-167. https://doi.org/10.1007/s10935-005-1849-y
Rhodes, J. E., Reddy, R., Grossman, J. B., and Lee, J. M. (2002). Volunteer mentoring relationships with minority youth: An analysis of same- versus cross-race matches. Journal of Applied Social Psychology, 32(10), 2114-2133. https://www.rhodeslab.org/wp-content/uploads/2016/04/rhodes-et-al-2002-same-versus-cross-race-matches.pdf
Rhodes, J. E. (2020). Older and wiser: New ideas for youth mentoring in the 21st century. Harvard University Press. https://www.hup.harvard.edu/books/9780674292277
