diff --git a/NEWS.md b/NEWS.md
index 582f24f99..8da711c30 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,6 @@
 # mlr3 (development version)
 
+* feat: Throw warning when prediction and measure type do not match.
 * fix: The `mlr_reflections` were broken when an extension package was not loaded on the workers.
   Extension packages must now register themselves in the `mlr_reflections$loaded_packages` field.
 
diff --git a/R/Measure.R b/R/Measure.R
index 649dd077c..a398c318e 100644
--- a/R/Measure.R
+++ b/R/Measure.R
@@ -194,7 +194,7 @@ Measure = R6Class("Measure",
     #'
     #' @return `numeric(1)`.
     score = function(prediction, task = NULL, learner = NULL, train_set = NULL) {
-      assert_measure(self, task = task, learner = learner)
+      assert_measure(self, task = task, learner = learner, prediction = prediction)
       assert_prediction(prediction, null.ok = "requires_no_prediction" %nin% self$properties)
 
       if ("requires_task" %in% self$properties && is.null(task)) {
diff --git a/R/assertions.R b/R/assertions.R
index cc5be49dc..af9dabf65 100644
--- a/R/assertions.R
+++ b/R/assertions.R
@@ -194,8 +194,9 @@ assert_predictable = function(task, learner) {
 
 #' @export
 #' @param measure ([Measure]).
+#' @param prediction ([Prediction]).
 #' @rdname mlr_assertions
-assert_measure = function(measure, task = NULL, learner = NULL, .var.name = vname(measure)) {
+assert_measure = function(measure, task = NULL, learner = NULL, prediction = NULL, .var.name = vname(measure)) {
   assert_class(measure, "Measure", .var.name = .var.name)
 
   if (!is.null(task)) {
@@ -236,6 +237,13 @@ assert_measure = function(measure, task = NULL, learner = NULL, .var.name = vnam
     }
   }
 
+  if (!is.null(prediction)) {
+    # same as above but works without learner e.g. measure$score(prediction)
+    if (measure$check_prerequisites != "ignore" && measure$predict_type %nin% prediction$predict_types) {
+      warningf("Measure '%s' is missing predict type '%s' of prediction", measure$id, measure$predict_type)
+    }
+  }
+
   invisible(measure)
 }
 
diff --git a/man/mlr_assertions.Rd b/man/mlr_assertions.Rd
index 008bdbf10..e88f7625d 100644
--- a/man/mlr_assertions.Rd
+++ b/man/mlr_assertions.Rd
@@ -62,6 +62,7 @@ assert_measure(
   measure,
   task = NULL,
   learner = NULL,
+  prediction = NULL,
   .var.name = vname(measure)
 )
 
@@ -115,14 +116,14 @@ Set of required task properties.}
 
 \item{measure}{(\link{Measure}).}
 
+\item{prediction}{(\link{Prediction}).}
+
 \item{measures}{(list of \link{Measure}).}
 
 \item{resampling}{(\link{Resampling}).}
 
 \item{resamplings}{(list of \link{Resampling}).}
 
-\item{prediction}{(\link{Prediction}).}
-
 \item{rr}{(\link{ResampleResult}).}
 
 \item{bmr}{(\link{BenchmarkResult}).}
diff --git a/tests/testthat/test_Measure.R b/tests/testthat/test_Measure.R
index 786c94b84..bb343dd64 100644
--- a/tests/testthat/test_Measure.R
+++ b/tests/testthat/test_Measure.R
@@ -188,3 +188,13 @@ test_that("checks on predict_sets", {
   expect_error({m$predict_sets = "imaginary"}, "Must be a subset")
 })
 
+test_that("measure and prediction type is checked", {
+  learner = lrn("classif.rpart")
+  task = tsk("pima")
+  learner$train(task)
+  pred = learner$predict(task)
+
+  measure = msr("classif.logloss")
+  expect_warning(measure$score(pred), "is missing predict type")
+})
+