diff --git a/R/conformal_infer_cv.R b/R/conformal_infer_cv.R
index 31910f6..b6ed4d4 100644
--- a/R/conformal_infer_cv.R
+++ b/R/conformal_infer_cv.R
@@ -33,7 +33,7 @@
 #' Rina Foygel Barber, Emmanuel J. Candès, Aaditya Ramdas, Ryan J. Tibshirani
 #' "Predictive inference with the jackknife+," _The Annals of Statistics_,
 #' 49(1), 486-507, 2021
-#' @examplesIf !probably:::is_cran_check()
+#' @examplesIf !probably:::is_cran_check() & rlang::is_installed(c("modeldata", "parsnip"))
 #' library(workflows)
 #' library(dplyr)
 #' library(parsnip)
diff --git a/R/conformal_infer_quantile.R b/R/conformal_infer_quantile.R
index 288ff8e..a933d2a 100644
--- a/R/conformal_infer_quantile.R
+++ b/R/conformal_infer_quantile.R
@@ -31,7 +31,7 @@
 #' @references
 #' Romano, Yaniv, Evan Patterson, and Emmanuel Candes. "Conformalized quantile
 #' regression." _Advances in neural information processing systems_ 32 (2019).
-#' @examplesIf !probably:::is_cran_check()
+#' @examplesIf !probably:::is_cran_check() & rlang::is_installed(c("modeldata", "parsnip", "quantregForest"))
 #' library(workflows)
 #' library(dplyr)
 #' library(parsnip)
diff --git a/R/conformal_infer_split.R b/R/conformal_infer_split.R
index b92e650..1b9d36a 100644
--- a/R/conformal_infer_split.R
+++ b/R/conformal_infer_split.R
@@ -28,7 +28,7 @@
 #' @references
 #' Lei, Jing, et al. "Distribution-free predictive inference for regression."
 #' _Journal of the American Statistical Association_ 113.523 (2018): 1094-1111.
-#' @examplesIf !probably:::is_cran_check()
+#' @examplesIf !probably:::is_cran_check() & rlang::is_installed(c("modeldata", "parsnip", "nnet"))
 #' library(workflows)
 #' library(dplyr)
 #' library(parsnip)
diff --git a/man/int_conformal_cv.Rd b/man/int_conformal_cv.Rd
index 7309cbd..dc3e66f 100644
--- a/man/int_conformal_cv.Rd
+++ b/man/int_conformal_cv.Rd
@@ -51,7 +51,7 @@ stop the computations for other types of resamples, but we have no way of
 knowing whether the results are appropriate.
 }
 \examples{
-\dontshow{if (!probably:::is_cran_check()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (!probably:::is_cran_check() & rlang::is_installed(c("modeldata", "parsnip"))) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(workflows)
 library(dplyr)
 library(parsnip)
diff --git a/man/int_conformal_quantile.Rd b/man/int_conformal_quantile.Rd
index cfc8907..4486985 100644
--- a/man/int_conformal_quantile.Rd
+++ b/man/int_conformal_quantile.Rd
@@ -46,7 +46,7 @@ Note that the because of the method used to construct the interval, it is
 possible that the prediction intervals will not include the predicted value.
 }
 \examples{
-\dontshow{if (!probably:::is_cran_check()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (!probably:::is_cran_check() & rlang::is_installed(c("modeldata", "parsnip", "quantregForest"))) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(workflows)
 library(dplyr)
 library(parsnip)
diff --git a/man/int_conformal_split.Rd b/man/int_conformal_split.Rd
index 262c3e9..7ca7563 100644
--- a/man/int_conformal_split.Rd
+++ b/man/int_conformal_split.Rd
@@ -45,7 +45,7 @@ quantile (e.g., the 95th for 95\% interval) and should not include rows that
 were in the original training set.
 }
 \examples{
-\dontshow{if (!probably:::is_cran_check()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (!probably:::is_cran_check() & rlang::is_installed(c("modeldata", "parsnip", "nnet"))) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(workflows)
 library(dplyr)
 library(parsnip)