diff --git a/R/plot.R b/R/plot.R
index 84aef0bb6..eff23634b 100644
--- a/R/plot.R
+++ b/R/plot.R
@@ -717,12 +717,11 @@ plot_predictions <- function(data = NULL,
     intervals[, quantile := NULL]
   }
 
+  pal <- grDevices::colorRampPalette(c("steelblue3", "lightskyblue1"))
+
   plot <- ggplot2::ggplot(data = data, aes(x = !!ggplot2::sym(x))) +
     ggplot2::scale_colour_manual("",values = c("black", "steelblue4")) +
-    ggplot2::scale_fill_manual("range", values = c("steelblue3",
-                                                   "lightskyblue3",
-                                                   "lightskyblue2",
-                                                   "lightskyblue1")) +
+    ggplot2::scale_fill_manual(name = "range", values = pal(length(range))) +
     ggplot2::theme_light()
 
   if (nrow(intervals) != 0) {
diff --git a/tests/testthat/test-plot_predictions.R b/tests/testthat/test-plot_predictions.R
index c5400179e..74537fb5e 100644
--- a/tests/testthat/test-plot_predictions.R
+++ b/tests/testthat/test-plot_predictions.R
@@ -16,3 +16,21 @@ test_that("plot_predictions() works with point forecasts", {
   vdiffr::expect_doppelganger('plot_predictions_point_forecasts', p)
 
 })
+
+test_that("plot_predictions() can handle an arbitrary number of quantiles", {
+
+  example2 <- scoringutils::range_example_data_long
+
+  p <- scoringutils::plot_predictions(
+    example2, x = "value_date",
+    filter_truth = list('value_date <= "2020-06-22"',
+                       'value_date > "2020-05-01"'),
+    filter_forecasts = list("model == 'SIRCOVID'",
+                           'creation_date == "2020-06-22"'),
+    allow_truth_without_pred = TRUE,
+    facet_formula = geography ~ value_desc,
+    range = c(0, 10, 20, 30, 40, 50, 60)
+  )
+
+  vdiffr::expect_doppelganger('plot_predictions_many_quantiles', p)
+})