diff --git a/monad-bayes.cabal b/monad-bayes.cabal
index e74b1fe9..fcd047b9 100644
--- a/monad-bayes.cabal
+++ b/monad-bayes.cabal
@@ -94,10 +94,14 @@ library
 
   default-extensions:
     BlockArguments
+    DerivingVia
     FlexibleContexts
+    GeneralizedNewtypeDeriving
     ImportQualifiedPost
+    KindSignatures
     LambdaCase
     OverloadedStrings
+    StandaloneDeriving
     TupleSections
 
   if flag(dev)
diff --git a/src/Control/Monad/Bayes/Class.hs b/src/Control/Monad/Bayes/Class.hs
index b11f3f86..d1d46e1d 100644
--- a/src/Control/Monad/Bayes/Class.hs
+++ b/src/Control/Monad/Bayes/Class.hs
@@ -71,6 +71,7 @@ module Control.Monad.Bayes.Class
     Measure,
     Kernel,
     Log (ln, Exp),
+    MonadMeasureTrans (..),
   )
 where
 
@@ -82,9 +83,11 @@ import Control.Monad.Identity (IdentityT)
 import Control.Monad.List (ListT)
 import Control.Monad.Reader (ReaderT)
 import Control.Monad.State (StateT)
+import Control.Monad.Trans (MonadTrans)
 import Control.Monad.Writer (WriterT)
 import Data.Histogram qualified as H
 import Data.Histogram.Fill qualified as H
+import Data.Kind (Type)
 import Data.Matrix
   ( Matrix,
     cholDecomp,
@@ -342,68 +345,82 @@ histogramToList = H.asList
 ----------------------------------------------------------------------------
 -- Instances that lift probabilistic effects to standard tranformers.
 
-instance MonadDistribution m => MonadDistribution (IdentityT m) where
-  random = lift random
-  bernoulli = lift . bernoulli
+deriving via (MonadMeasureTrans IdentityT m) instance MonadDistribution m => MonadDistribution (IdentityT m)
 
-instance MonadFactor m => MonadFactor (IdentityT m) where
-  score = lift . score
+deriving via (MonadMeasureTrans IdentityT m) instance MonadFactor m => MonadFactor (IdentityT m)
 
 instance MonadMeasure m => MonadMeasure (IdentityT m)
 
-instance MonadDistribution m => MonadDistribution (ExceptT e m) where
-  random = lift random
-  uniformD = lift . uniformD
+deriving via (MonadMeasureTrans (ExceptT e) m) instance MonadDistribution m => MonadDistribution (ExceptT e m)
 
-instance MonadFactor m => MonadFactor (ExceptT e m) where
-  score = lift . score
+deriving via (MonadMeasureTrans (ExceptT e) m) instance MonadFactor m => MonadFactor (ExceptT e m)
 
 instance MonadMeasure m => MonadMeasure (ExceptT e m)
 
-instance MonadDistribution m => MonadDistribution (ReaderT r m) where
-  random = lift random
-  bernoulli = lift . bernoulli
+deriving via (MonadMeasureTrans (ReaderT r) m) instance MonadDistribution m => MonadDistribution (ReaderT r m)
 
-instance MonadFactor m => MonadFactor (ReaderT r m) where
-  score = lift . score
+deriving via (MonadMeasureTrans (ReaderT r) m) instance MonadFactor m => MonadFactor (ReaderT r m)
 
 instance MonadMeasure m => MonadMeasure (ReaderT r m)
 
-instance (Monoid w, MonadDistribution m) => MonadDistribution (WriterT w m) where
-  random = lift random
-  bernoulli = lift . bernoulli
-  categorical = lift . categorical
+deriving via (MonadMeasureTrans (WriterT w) m) instance (Monoid w, MonadDistribution m) => MonadDistribution (WriterT w m)
 
-instance (Monoid w, MonadFactor m) => MonadFactor (WriterT w m) where
-  score = lift . score
+deriving via (MonadMeasureTrans (WriterT w) m) instance (Monoid w, MonadFactor m) => MonadFactor (WriterT w m)
 
 instance (Monoid w, MonadMeasure m) => MonadMeasure (WriterT w m)
 
-instance MonadDistribution m => MonadDistribution (StateT s m) where
-  random = lift random
-  bernoulli = lift . bernoulli
-  categorical = lift . categorical
-  uniformD = lift . uniformD
+deriving via (MonadMeasureTrans (StateT s) m) instance MonadDistribution m => MonadDistribution (StateT s m)
 
-instance MonadFactor m => MonadFactor (StateT s m) where
-  score = lift . score
+deriving via (MonadMeasureTrans (StateT s) m) instance MonadFactor m => MonadFactor (StateT s m)
 
 instance MonadMeasure m => MonadMeasure (StateT s m)
 
-instance MonadDistribution m => MonadDistribution (ListT m) where
-  random = lift random
-  bernoulli = lift . bernoulli
-  categorical = lift . categorical
+deriving via (MonadMeasureTrans ListT m) instance MonadDistribution m => MonadDistribution (ListT m)
 
-instance MonadFactor m => MonadFactor (ListT m) where
-  score = lift . score
+deriving via (MonadMeasureTrans ListT m) instance MonadFactor m => MonadFactor (ListT m)
 
 instance MonadMeasure m => MonadMeasure (ListT m)
 
-instance MonadDistribution m => MonadDistribution (ContT r m) where
+deriving via (MonadMeasureTrans (ContT r) m) instance MonadDistribution m => MonadDistribution (ContT r m)
+
+deriving via (MonadMeasureTrans (ContT r) m) instance MonadFactor m => MonadFactor (ContT r m)
+
+instance MonadMeasure m => MonadMeasure (ContT r m)
+
+-- * Utility for deriving MonadDistribution, MonadFactor and MonadMeasure
+
+-- | Newtype to derive 'MonadDistribution', 'MonadFactor' and 'MonadMeasure' automatically for monad transformers.
+--
+-- The typical usage is with the `StandaloneDeriving` and `DerivingVia` extensions.
+-- For example, to derive all instances for the 'IdentityT' transformer, one writes:
+--
+-- @
+-- deriving via (MonadMeasureTrans IdentityT m) instance MonadDistribution m => MonadDistribution (IdentityT m)
+-- deriving via (MonadMeasureTrans IdentityT m) instance MonadFactor m => MonadFactor (IdentityT m)
+-- instance MonadMeasure m => MonadMeasure (IdentityT m)
+-- @
+-- (The final 'MonadMeasure' could also be derived `via`, but this isn't necessary because it doesn't contain any methods.)
+newtype MonadMeasureTrans (t :: (Type -> Type) -> Type -> Type) (m :: Type -> Type) a = MonadMeasureTrans {getMonadMeasureTrans :: t m a}
+  deriving (Functor, Applicative, Monad)
+
+instance MonadTrans t => MonadTrans (MonadMeasureTrans t) where
+  lift = MonadMeasureTrans . lift
+
+instance (MonadTrans t, MonadDistribution m, Monad (t m)) => MonadDistribution (MonadMeasureTrans t m) where
   random = lift random
+  uniform = (lift .) . uniform
+  normal = (lift .) . normal
+  gamma = (lift .) . gamma
+  beta = (lift .) . beta
+  bernoulli = lift . bernoulli
+  categorical = lift . categorical
+  logCategorical = lift . logCategorical
+  uniformD = lift . uniformD
+  geometric = lift . geometric
+  poisson = lift . poisson
+  dirichlet = lift . dirichlet
 
-instance MonadFactor m => MonadFactor (ContT r m) where
+instance (MonadFactor m, MonadTrans t, Monad (t m)) => MonadFactor (MonadMeasureTrans t m) where
   score = lift . score
 
-instance MonadMeasure m => MonadMeasure (ContT r m)
+instance (MonadDistribution m, MonadFactor m, MonadTrans t, Monad (t m)) => MonadMeasure (MonadMeasureTrans t m)
diff --git a/src/Control/Monad/Bayes/Inference/SMC2.hs b/src/Control/Monad/Bayes/Inference/SMC2.hs
index 3b8a3787..c5608dda 100644
--- a/src/Control/Monad/Bayes/Inference/SMC2.hs
+++ b/src/Control/Monad/Bayes/Inference/SMC2.hs
@@ -20,7 +20,7 @@ module Control.Monad.Bayes.Inference.SMC2
 where
 
 import Control.Monad.Bayes.Class
-  ( MonadDistribution (random),
+  ( MonadDistribution,
     MonadFactor (..),
     MonadMeasure,
   )
@@ -35,7 +35,7 @@ import Numeric.Log (Log)
 
 -- | Helper monad transformer for preprocessing the model for 'smc2'.
 newtype SMC2 m a = SMC2 (Sequential (Traced (Population m)) a)
-  deriving newtype (Functor, Applicative, Monad)
+  deriving newtype (Functor, Applicative, Monad, MonadDistribution, MonadFactor)
 
 setup :: SMC2 m a -> Sequential (Traced (Population m)) a
 setup (SMC2 m) = m
@@ -43,12 +43,6 @@ setup (SMC2 m) = m
 instance MonadTrans SMC2 where
   lift = SMC2 . lift . lift . lift
 
-instance MonadDistribution m => MonadDistribution (SMC2 m) where
-  random = lift random
-
-instance Monad m => MonadFactor (SMC2 m) where
-  score = SMC2 . score
-
 instance MonadDistribution m => MonadMeasure (SMC2 m)
 
 -- | Sequential Monte Carlo squared.
diff --git a/src/Control/Monad/Bayes/Sequential/Coroutine.hs b/src/Control/Monad/Bayes/Sequential/Coroutine.hs
index d15c38f8..81a7b621 100644
--- a/src/Control/Monad/Bayes/Sequential/Coroutine.hs
+++ b/src/Control/Monad/Bayes/Sequential/Coroutine.hs
@@ -26,9 +26,10 @@ module Control.Monad.Bayes.Sequential.Coroutine
 where
 
 import Control.Monad.Bayes.Class
-  ( MonadDistribution (bernoulli, categorical, random),
+  ( MonadDistribution,
     MonadFactor (..),
     MonadMeasure,
+    MonadMeasureTrans (..),
   )
 import Control.Monad.Coroutine
   ( Coroutine (..),
@@ -54,10 +55,7 @@ newtype Sequential m a = Sequential {runSequential :: Coroutine (Await ()) m a}
 extract :: Await () a -> a
 extract (Await f) = f ()
 
-instance MonadDistribution m => MonadDistribution (Sequential m) where
-  random = lift random
-  bernoulli = lift . bernoulli
-  categorical = lift . categorical
+deriving via (MonadMeasureTrans Sequential m) instance MonadDistribution m => MonadDistribution (Sequential m)
 
 -- | Execution is 'suspend'ed after each 'score'.
 instance MonadFactor m => MonadFactor (Sequential m) where