🐾 Name My Pet

Most popular Korean Jindo names

The names real owners gave 99 Korean Jindos in public license and shelter records.

Top 93 names

  1. Kona3
  2. Nala2
  3. Kuma2
  4. Sonny2
  5. Kkaebi2
  6. Jasmine1
  7. Mel1
  8. Shadow1
  9. Raven1
  10. Daisy1
  11. Miko1
  12. Mango1
  13. Pierogi1
  14. Cherry1
  15. Shelly1
  16. Rin1
  17. Hera1
  18. Mari1
  19. Dasom1
  20. Evoolek1
  21. Joy1
  22. Blue Didi Haase1
  23. Miso1
  24. Matcha1
  25. Skye1
  26. Mitsu1
  27. Kkomi1
  28. Kira1
  29. Arang1
  30. Sugar1
  31. Hazel1
  32. Chuy Nibbles1
  33. Suni1
  34. Maisie1
  35. Mila1
  36. Yoshi1
  37. Zero1
  38. Alfie Mason1
  39. Ryan1
  40. Toggle1
  41. Julian1
  42. Billy1
  43. Louie1
  44. Pepper1
  45. Mochi1
  46. Shisa1
  47. Rain1
  48. Otis1
  49. Odin1
  50. Dart1
  51. Moki1
  52. Apollo1
  53. Mando1
  54. Barley1
  55. Stars Joey1
  56. Kobe1
  57. Kupo1
  58. Kimchi1
  59. Bash1
  60. Harrison1
  61. Watson1
  62. Pumpkin1
  63. Malu1
  64. Matsu1
  65. Coro1
  66. Leny1
  67. Zeke1
  68. Simon1
  69. Flapjack1
  70. Mica1
  71. Cloud1
  72. Eagle1
  73. Frankie1
  74. Pluto1
  75. Kiba1
  76. Koji1
  77. Mocha1
  78. Twyla1
  79. Izzy1
  80. Nishoko1
  81. Moon1
  82. Mars Potvin1
  83. Tofu1
  84. Sesame Park1
  85. Ravi1
  86. Genie1
  87. Yuki1
  88. Lebu1
  89. Popcorn1
  90. Arlo1
  91. Maple1
  92. Nori1
  93. Piper1
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Counts come from public open data: NYC Dog Licensing Dataset (NYC Open Data); Seattle Pet Licenses (public domain); Dogs of Cambridge (ODC PDDL); Licensed Dog and Cat Names, City of Toronto (Open Government Licence – Toronto); Hundenamen, Stadt Zürich (Open Data Zürich); Dog Registrations, City of Adelaide (CC BY 3.0 AU); Burnside Dog Registrations (CC BY 3.0 AU); City of Prospect Dog Registrations (CC BY 3.0 AU); Pet Licenses, City of Richmond; Animal Shelter Intake and Outcome, County of Sonoma; Austin Animal Center Outcomes (public domain). License records count registered pets; shelter records count animals that passed through a shelter (some names are given by staff). Pets that appear in several years of one dataset are counted once. Names are counted as written, so spelling variants are separate.