diff --git a/R/aaa_models.R b/R/aaa_models.R
index 112d5b225..957d6a029 100644
--- a/R/aaa_models.R
+++ b/R/aaa_models.R
@@ -280,12 +280,27 @@ check_pred_info <- function(pred_obj, type) {
   invisible(NULL)
 }
 
+check_spec_pred_type <- function(object, type) {
+  possible_preds <- names(object$spec$method$pred)
+  if (!any(possible_preds == type)) {
+    rlang::abort(c(
+      glue::glue("No {type} prediction method available for this model."),
+      glue::glue("Value for `type` should be one of: ",
+                 glue::glue_collapse(glue::glue("'{possible_preds}'"), sep = ", "))
+    ))
+  }
+  invisible(NULL)
+}
+
+
 check_pkg_val <- function(pkg) {
-  if (rlang::is_missing(pkg) || length(pkg) != 1 || !is.character(pkg))
+  if (rlang::is_missing(pkg) || length(pkg) != 1 || !is.character(pkg)) {
     rlang::abort("Please supply a single character value for the package name.")
+  }
   invisible(NULL)
 }
 
+
 check_interface_val <- function(x) {
   exp_interf <- c("data.frame", "formula", "matrix")
   if (length(x) != 1 || !(x %in% exp_interf)) {
diff --git a/R/predict_class.R b/R/predict_class.R
index 6e777b329..e96d460b1 100644
--- a/R/predict_class.R
+++ b/R/predict_class.R
@@ -12,8 +12,7 @@ predict_class.model_fit <- function(object, new_data, ...) {
   if (object$spec$mode != "classification")
     rlang::abort("`predict.model_fit()` is for predicting factor outcomes.")
 
-  if (!any(names(object$spec$method$pred) == "class"))
-    rlang::abort("No class prediction module defined for this model.")
+  check_spec_pred_type(object, "class")
 
   if (inherits(object$fit, "try-error")) {
     rlang::warn("Model fit failed; cannot make predictions.")
diff --git a/R/predict_classprob.R b/R/predict_classprob.R
index 6dcb4d897..5d8f2cf05 100644
--- a/R/predict_classprob.R
+++ b/R/predict_classprob.R
@@ -9,8 +9,8 @@ predict_classprob.model_fit <- function(object, new_data, ...) {
   if (object$spec$mode != "classification")
     rlang::abort("`predict.model_fit()` is for predicting factor outcomes.")
 
-  if (!any(names(object$spec$method$pred) == "prob"))
-    rlang::abort("No class probability module defined for this model.")
+  check_spec_pred_type(object, "prob")
+
 
   if (inherits(object$fit, "try-error")) {
     rlang::warn("Model fit failed; cannot make predictions.")
diff --git a/R/predict_hazard.R b/R/predict_hazard.R
index e090cb85d..d70217cba 100644
--- a/R/predict_hazard.R
+++ b/R/predict_hazard.R
@@ -7,8 +7,7 @@
 predict_hazard.model_fit <-
   function(object, new_data, .time, ...) {
 
-    if (is.null(object$spec$method$pred$hazard))
-      rlang::abort("No hazard prediction method defined for this engine.")
+    check_spec_pred_type(object, "hazard")
 
     if (inherits(object$fit, "try-error")) {
       rlang::warn("Model fit failed; cannot make predictions.")
diff --git a/R/predict_interval.R b/R/predict_interval.R
index 7dd8562c1..018228cdd 100644
--- a/R/predict_interval.R
+++ b/R/predict_interval.R
@@ -10,8 +10,7 @@
 #' @export
 predict_confint.model_fit <- function(object, new_data, level = 0.95, std_error = FALSE, ...) {
 
-  if (is.null(object$spec$method$pred$conf_int))
-    rlang::abort("No confidence interval method defined for this engine.")
+  check_spec_pred_type(object, "conf_int")
 
   if (inherits(object$fit, "try-error")) {
     rlang::warn("Model fit failed; cannot make predictions.")
@@ -58,8 +57,7 @@ predict_confint <- function(object, ...)
 # @export
 predict_predint.model_fit <- function(object, new_data, level = 0.95, std_error = FALSE, ...) {
 
-  if (is.null(object$spec$method$pred$pred_int))
-    rlang::abort("No prediction interval method defined for this engine.")
+  check_spec_pred_type(object, "pred_int")
 
   if (inherits(object$fit, "try-error")) {
     rlang::warn("Model fit failed; cannot make predictions.")
diff --git a/R/predict_linear_pred.R b/R/predict_linear_pred.R
index c0a7abc92..62af94f44 100644
--- a/R/predict_linear_pred.R
+++ b/R/predict_linear_pred.R
@@ -6,8 +6,7 @@
 #' @export
 predict_linear_pred.model_fit <- function(object, new_data, ...) {
 
-  if (!any(names(object$spec$method$pred) == "linear_pred"))
-    rlang::abort("No prediction module defined for this model.")
+  check_spec_pred_type(object, "linear_pred")
 
   if (inherits(object$fit, "try-error")) {
     rlang::warn("Model fit failed; cannot make predictions.")
diff --git a/R/predict_numeric.R b/R/predict_numeric.R
index 38fce1a39..17d61a614 100644
--- a/R/predict_numeric.R
+++ b/R/predict_numeric.R
@@ -10,8 +10,7 @@ predict_numeric.model_fit <- function(object, new_data, ...) {
                             "Use `predict_class()` or `predict_classprob()` for ",
                             "classification models."))
 
-  if (!any(names(object$spec$method$pred) == "numeric"))
-    rlang::abort("No prediction module defined for this model.")
+  check_spec_pred_type(object, "numeric")
 
   if (inherits(object$fit, "try-error")) {
     rlang::warn("Model fit failed; cannot make predictions.")
diff --git a/R/predict_quantile.R b/R/predict_quantile.R
index 9d671af24..7965069e6 100644
--- a/R/predict_quantile.R
+++ b/R/predict_quantile.R
@@ -9,8 +9,7 @@
 predict_quantile.model_fit <-
   function(object, new_data, quantile = (1:9)/10, ...) {
 
-    if (is.null(object$spec$method$pred$quantile))
-      rlang::abort("No quantile prediction method defined for this engine.")
+    check_spec_pred_type(object, "quantile")
 
     if (inherits(object$fit, "try-error")) {
       rlang::warn("Model fit failed; cannot make predictions.")
diff --git a/R/predict_raw.R b/R/predict_raw.R
index 22e59b792..cf391a063 100644
--- a/R/predict_raw.R
+++ b/R/predict_raw.R
@@ -13,8 +13,7 @@ predict_raw.model_fit <- function(object, new_data, opts = list(), ...) {
       c(object$spec$method$pred$raw$args, opts)
   }
 
-  if (!any(names(object$spec$method$pred) == "raw"))
-    rlang::abort("No raw prediction module defined for this model.")
+  check_spec_pred_type(object, "raw")
 
   if (inherits(object$fit, "try-error")) {
     rlang::warn("Model fit failed; cannot make predictions.")
diff --git a/R/predict_survival.R b/R/predict_survival.R
index a3075fd66..536d800eb 100644
--- a/R/predict_survival.R
+++ b/R/predict_survival.R
@@ -7,8 +7,7 @@
 predict_survival.model_fit <-
   function(object, new_data, .time, ...) {
 
-    if (is.null(object$spec$method$pred$survival))
-      rlang::abort("No survival prediction method defined for this engine.")
+    check_spec_pred_type(object, "survival")
 
     if (inherits(object$fit, "try-error")) {
       rlang::warn("Model fit failed; cannot make predictions.")
diff --git a/R/predict_time.R b/R/predict_time.R
index fc96c6207..cdedda287 100644
--- a/R/predict_time.R
+++ b/R/predict_time.R
@@ -10,8 +10,7 @@ predict_time.model_fit <- function(object, new_data, ...) {
                             "Use `predict_class()` or `predict_classprob()` for ",
                             "classification models."))
 
-  if (!any(names(object$spec$method$pred) == "time"))
-    rlang::abort("No prediction module defined for this model.")
+  check_spec_pred_type(object, "time")
 
   if (inherits(object$fit, "try-error")) {
     rlang::warn("Model fit failed; cannot make predictions.")
diff --git a/R/svm_linear_data.R b/R/svm_linear_data.R
index 2778eff1c..25da85477 100644
--- a/R/svm_linear_data.R
+++ b/R/svm_linear_data.R
@@ -123,27 +123,6 @@ set_pred(
       )
   )
 )
-set_pred(
-  model = "svm_linear",
-  eng = "LiblineaR",
-  mode = "classification",
-  type = "prob",
-  value = list(
-    pre = function(x, object) {
-      rlang::abort(
-        paste0("The LiblineaR engine does not support class probabilities ",
-               "for any `svm` models.")
-      )
-    },
-    post = NULL,
-    func = c(fun = "predict"),
-    args =
-      list(
-        object = quote(object$fit),
-        newx = expr(as.matrix(new_data))
-      )
-  )
-)
 set_pred(
   model = "svm_linear",
   eng = "LiblineaR",
diff --git a/tests/testthat/test_svm_linear.R b/tests/testthat/test_svm_linear.R
index 24d4ced4a..cf6875079 100644
--- a/tests/testthat/test_svm_linear.R
+++ b/tests/testthat/test_svm_linear.R
@@ -280,12 +280,12 @@ test_that('linear svm classification prediction: LiblineaR', {
 
   expect_error(
     predict(cls_form, hpc_no_m[ind, -5], type = "prob"),
-    "The LiblineaR engine does not support class probabilities"
+    "No prob prediction method available for this model"
   )
 
   expect_error(
     predict(cls_xy_form, hpc_no_m[ind, -5], type = "prob"),
-    "The LiblineaR engine does not support class probabilities"
+    "No prob prediction method available for this model"
   )
 
 })