Key Takeaways
- In livestock cloning commercialization, the number of cloned animals produced remained small relative to the total herd population, with cloned cattle estimated at ~1 million by 2012 globally (2012 estimate).
- 0.7% of U.S. respondents said they would definitely buy cloned meat if it were available, showing low stated adoption intent in survey findings (U.S. survey).
- In the same 2009 U.S. consumer survey, 28% of respondents believed cloned meat should be banned, indicating measurable policy support for prohibition (survey).
- An EFSA-commissioned risk assessment framework distinguishes risks by life stage and process step, and identifies increased rates of abnormality for cloned animals relative to controls (structured risk characterization).
- The UK HFEA allows therapeutic cloning research under strict licensing but bans reproductive cloning, reflected in legal intent separating therapeutic vs reproductive use (statutory split).
- The International Society for Stem Cell Research (ISSCR) in its 2021 guidelines emphasized the need for governance of embryo research, including restrictions tied to human cloning-related derivations (guideline year).
- The EFSA opinion cited a low efficiency and high number of failed pregnancies as central to cloning’s animal welfare concerns, implying a measurable stage-failure burden (reviewed outcome).
- In a 2020 peer-reviewed study, cloned animals exhibited higher rates of placental abnormalities than conventionally produced controls, affecting successful gestation outcomes (study result).
- A 2018 study reported that epigenetic marks (e.g., DNA methylation) are often not fully reset in SCNT embryos, which correlates with abnormal development outcomes (measured epigenetic metric changes).
- In 2013, California’s SB 509 required labeling of cloned animal products, implying an added cost and operational step tied to state labeling compliance (law effective year and requirement).
- The U.S. National Academies reported that cloning livestock is expensive relative to conventional breeding, with cost-effectiveness constrained by low efficiency (assessment year 2016).
- A 2019 systematic assessment described that SCNT costs include lab consumables, technician time, and animal housing for many failed reconstructions, driving high per-birth cost relative to conventional breeding.
- Grand View Research projected the animal cloning market to reach $?? by 2028 with CAGR data (market forecast provides measurable growth).
- The pet cloning market forecast in a vendor report indicates a CAGR in the high single digits, reflecting growth expectations for services (forecast metric).
- A 2020 peer-reviewed meta-analysis reported that SCNT is associated with increased pregnancy loss compared with noncloned controls across mammals studied
Cloning remains costly and inefficient, with limited consumer demand and heightened pregnancy and placental risks.
Related reading
01 · Category
Industry Trends6 stats
Industry Trends Interpretation
02 · Category
Regulatory & Compliance5 stats
Regulatory & Compliance Interpretation
03 · Category
Performance Metrics5 stats
Performance Metrics Interpretation
04 · Category
Cost Analysis4 stats
Cost Analysis Interpretation
05 · Category
Market Size2 stats
Market Size Interpretation
06 · Category
Industry Overview5 stats
Industry Overview Interpretation
Cloning adoption: low consumer intent, stronger policy opposition
Survey data show limited consumer willingness to buy cloned meat, alongside substantial support for banning cloned meat.
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Rachel Svensson. (2026, February 13). Cloning Statistics. Gitnux. https://gitnux.org/cloning-statistics
Rachel Svensson. "Cloning Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/cloning-statistics.
Rachel Svensson. 2026. "Cloning Statistics." Gitnux. https://gitnux.org/cloning-statistics.
Sources & references
27 datasets cited across this report · attribution is report-level
+9 additional datasets cited (not shown individually)

